@article{ieeebibJ1, title={Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients}, author = {A. Ratnaweera and S.K. Halgamuge and H.C. Watson}, journal={IEEE Transactions on Evolutionary Computation}, volume= 8, issue= 3, date={ June 2004}, page={240 - 255 }, year={2004}, abstract={This paper introduces a novel parameter automation strategy for the particle swarm algorithm and two further extensions to improve its performance after a predefined number of generations. Initially, to efficiently control the local search and conver.....} } @TechReport{poli07:_analy_public_partic_swarm_optim_applic, author = {Riccardo Poli}, title = {An Analysis of Publications on Particle Swarm Optimization Applications}, institution = {Department of Computing and Electronic Systems, University of Essex}, year = 2007, number = {CSM-469}, month = {May}, note = {Revised November 2007} } @inproceedings{ieeebib10, title={ Image Classification using Chaotic Particle Swarm Optimization}, author = {K. Chandramouli and E. Izquierdo}, booktitle={2006 IEEE International Conference on Image Processing}, notes={Oct. 2006}, year={2006}, pages={3001 - 3004}, abstract={Particle Swarm Optimization is one of several meta-heuristic algorithms inspired by biological systems. The chaotic modeling of particle swarm optimization is presented in this paper with application to image classification. The performance of this m..... } } @inproceedings{ieeebib100, title={ Optimal PID controller design in PMSM servo system via particle swarm optimization}, author = {Haibing Hu and Qingbo Hu and Zhengyu Lu and Dehong Xu}, booktitle={Industrial Electronics Society, 2005. IECON 2005. 32nd Annual Conference of IEEE}, notes={6-10 Nov. 2005}, year={2005}, pages={5 pp. }, abstract={A novel PID controller design method is proposed in the paper for PMSM Servo system using particle swarm optimization (PSO). The detailed procedures for optimal PID controller design are summarized in terms of the principle of particle swarm optimiza..... } } @inproceedings{ieeebib1000, title={ Particle Swarm Optimization of Frequency Selective Surfaces for the Design of Artificial Magnetic Conductors}, author = {S. Genovesi and R. Mittra and A. Monorchio and G. Manara}, booktitle={Antennas and Propagation Society International Symposium 2006, IEEE}, notes={9-14 July 2006}, year={2006}, pages={3519 - 3522 }, abstract={Not available.....} } @inproceedings{ieeebib1001, title={ On the Efficiency of Particle Swarm Optimizer when Applied to Antenna Optimization}, author = {D.I. Olcan and R.M. Golubovic and B.M. Kolundzija}, booktitle={Antennas and Propagation Society International Symposium 2006, IEEE}, notes={9-14 July 2006}, year={2006}, pages={3297 - 3300 }, abstract={Not available.....} } @inproceedings{ieeebib1002, title={ Multi-objective Particle Swarm Optimization for High Performance Array and Reflector Antennas}, author = {Shenheng Xu and Y. Rahmat-Samii}, booktitle={Antennas and Propagation Society International Symposium 2006, IEEE}, notes={9-14 July 2006}, year={2006}, pages={3293 - 3296 }, abstract={Not available.....} } @inproceedings{ieeebib1003, title={ Cluster Distance Factor Searching by Particle Swarm Optimization for Self-Growing Radial Basis Function Neural Network}, author = {Chun-Ling Lin and Sheng-Ta Hsieh and Tsung-Ying Sun and Chan-Cheng Liu}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={4825 - 4830 }, abstract={A very important step for the RBF network training is to decide a proper number of hidden nodes. This paper proposes a PSO-based algorithm for searching optimal cluster distance factor. Thus, the self-growing RBF network training algorithm can be rea.....} } @inproceedings{ieeebib1004, title={ A PSO and Simulated Annealing Hybrid Algorithm to Task Allocation Problem for Holonic Manufacturing System}, author = {Yahong Yang and Fuqing Zhao and Yunping Yao and Aihong Zhu}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006. }, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6767 - 6771 }, abstract={This paper focuses on the dynamic re-configuration and task optimization of holonic manufacturing systems (HMS). The concept of dynamic virtual clustering is extended to the control process of a holarchy or holonic organization. The mediator-based dy.....} } @inproceedings{ieeebib1005, title={ Digital Implementation of DTC Based on PSO for Induction Motors}, author = {Chengzhi Cao and Bo Zhou and Min Li and Jing Du}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006. }, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6349 - 6352 }, abstract={A novel scheme for direct torque control(DTC) using Particle Swarm Optimization(PSO) was proposed. The PSO was used to adjust the parameters (Kp,Ki,Kd) of PID controller. The scheme improve the adjustive capability of PID controller. PSO-PID controll.....} } @inproceedings{ieeebib1006, title={ Control of Networked Robotic Manipulator via ILC and Minimum Entropy}, author = {Jianhua Zhang and Hong Wang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006. }, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={9499 - 9503 }, abstract={This paper presents a novel feedback control method for networked control systems by combining the P-type iterative learning control (ILC) idea with minimum tracking error entropy control strategy. In specific, the time-delayed control system of robo.....} } @inproceedings{ieeebib1007, title={ A PSO-Based Method for Traffic Stop-Sign Detection}, author = {Hang Zhang and Dayong Luo}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006.}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={8625 - 8629 }, abstract={This paper developed a new technology for the detection of traffic stop-sign from a motion picture captured by a CCD camera in a car. Firstly original image was segmented in YCbCr color model by the threshold of characteristic color of traffic stop-s.....} } @inproceedings{ieeebib1008, title={ A Nested Neighborhood PSO Algorithm for Multi-modal Function Optimization}, author = {Guangyu Lian and Chundi Mu and Zengqi Sun}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006. }, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3690 - 3694 }, abstract={In PSO algorithm, a nested neighborhood model was proposed for multi-modal function optimization. First, a local structure was constructed for each particle under a predefined Euclidian distance measure(called peak-granularity). Then a nesting mechan.....} } @inproceedings{ieeebib1009, title={ Parameters selection for SVR based on PSO}, author = {Qun Zong and Wenjing Liu and Liqian Dou}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006. }, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={2811 - 2814 }, abstract={Support vector machine (SVM) has recently emerged as a powerful technique for solving problems in pattern classification and regression, but its performance mainly depends on the parameters selection of it. Parameters selection for SVM is very comple.....} } @inproceedings{ieeebib101, title={ An improved particle swarm optimization algorithm for optimal reactive power dispatch}, author = {B. Zhao and C.X. Guo and Y.J. Cao}, booktitle={Power Engineering Society General Meeting, 2005. IEEE}, notes={12-16 June 2005}, year={2005}, pages={272 - 279 Vol. 1 }, abstract={This paper presents an improved particle swarm optimization algorithm (IPSO) to optimal reactive power dispatch and voltage control of power systems. The improved particle swarm optimization approach uses more particles' information to control the mu..... } } @inproceedings{ieeebib1010, title={ Application of Snake Model Based on PSO in the Image Segmentation}, author = {Kejun Wang and Qingchang Guo and Dayan Zhuang and Hongxia Chu and Bin Fu}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006. }, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={9637 - 9640 }, abstract={For exactly segmenting the object in the image, an algorithm of image segmentation according to PSO (Particle Swarm Optimization) and snake model was proposed. The PSO has some advantages, such as the global optimization, sensitive degree low for noi.....} } @inproceedings{ieeebib1011, title={ Application of Improved PSO for CSI in Customization System Oriented Network Manufacturing}, author = {Jia Liu and Hongtao Yu and Yadong Gong and Wanshan Wang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006. }, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7944 - 7947 }, abstract={A mathematical model of Customer Satisfaction Index (CSI) in individualized product customization system is put forward in this paper, which bases on networked manufacturing platform. The problem of customer satisfaction index in terms of this model .....} } @inproceedings{ieeebib1012, title={ Global Optimal ICA and its Application in Brain MEG Data Analysis}, author = {Lei Xie and Liying Jiang}, booktitle={International Conference on Neural Networks and Brain, 2005. ICNN\&B '05. }, notes={Volume 1, 13-15 Oct. 2005}, year={2005}, pages={353 - 357 }, abstract={Due to its ability to recover the unobserved signals or sources from mixed observations, as well as its ability to analyze the high order statistics of observed signals, ICA has been widely adopted to analyze the brain image data, financial time seri.....} } @inproceedings{ieeebib1013, title={ A Recognition Method of Reduced Evolutionary Neural Network and Its Application}, author = {Kewen Xia and Zhiwei Zhang and Mingxiao Liu and Ruixia Yang}, booktitle={International Conference on Neural Networks and Brain, 2005. ICNN\&B '05. }, notes={Volume 1, 13-15 Oct. 2005}, year={2005}, pages={343 - 348 }, abstract={In complex pattern recognition, it is difficult to evaluate by traditional method or single intelligent method. So a recognition method of reduced evolutionary neural network is presented, which includes, an algorithm for continuous attribute discret.....} } @inproceedings{ieeebib1014, title={ Face Recognition Using DCT and Hybrid Flexible Neural Tree}, author = {Yuehui Chen and Shuyan Jiang and A. Abraham}, booktitle={International Conference on Neural Networks and Brain, 2005. ICNN\&B '05. }, notes={Volume 3, 13-15 Oct. 2005}, year={2005}, pages={1459 - 1463 }, abstract={This paper proposes a new face recognition approach by using the Discrete Cosine Transform (DCT) and hybrid flexible neural tree (FNT) classification model. The DCT is employed to extract the input features to build a face recognition system, and the.....} } @inproceedings{ieeebib1015, title={ Particle Swarm Optimizer with Integral Controller}, author = {Jianchao Zeng and Zbihua Cui}, booktitle={International Conference on Neural Networks and Brain, 2005. ICNN\&B '05. }, notes={Volume 3, 13-15 Oct. 2005}, year={2005}, pages={1840 - 1842 }, abstract={TRhe evoluionary equations of PSO are secondorder discree ime hear stochastic system. It can be regarded as a control plant, and Intreducing a controller to regulate the dynamic evolutionary behaviors of PSO. In the paper, z-transformation is used to.....} } @inproceedings{ieeebib1016, title={ Timetable Scheduling Using Particle Swarm Optimization}, author = {Shu-Chuan Chu and Yi-Tin Chen and Jiun-Huei Ho}, booktitle={First International Conference on Innovative Computing, Information and Control, 2006. ICICIC '06. }, notes={Volume 3, 30-01 Aug. 2006}, year={2006}, pages={324 - 327 }, abstract={In timetable scheduling problems, examination subjects must be slotted to certain times that satisfy several of constraints. They are NP-completeness problems, which usually lead to satisfactory but suboptimal solutions. As PSO has many successful ap.....} } @inproceedings{ieeebib1017, title={ Particle Swarm Optimization for Control of Nonlinear Dynamics}, author = {Jiann-Horng Lin}, booktitle={First International Conference on Innovative Computing, Information and Control, 2006. ICICIC '06. }, notes={Volume 1, 30-01 Aug. 2006}, year={2006}, pages={542 - 545 }, abstract={Chaos control refers to any form of manipulation of chaotic dynamical behavior exhibited by complex nonlinear systems. A chaotic system in general cannot be made to converge to a freely evolving desired trajectory, whether periodic or chaotic, becaus.....} } @inproceedings{ieeebib1018, title={ Ima e Enhancement sin redator- rey ptimi er Al orithm}, author = {M. Noura and M. Batouche}, booktitle={Information and Communication Technologies, 2006. ICTTA '06. 2nd}, notes={Volume 1, 24-28 April 2006}, year={2006}, pages={1584 - 1589 }, abstract={In, this paper, we describe the implementation and performance of a novel approach applied to image contrast enhancement. This new algorithm is the extension of Particle Swarm ptimisation (PS ). This algorithm, which is called Predator Prey ptimisati.....} } @inproceedings{ieeebib1019, title={ Active Contour Optimization using Particle Swarm Optimizer}, author = {M.A. Asl and S.A. Seyedin}, booktitle={Information and Communication Technologies, 2006. ICTTA '06. 2nd}, notes={Volume 1, 24-28 April 2006}, year={2006}, pages={1522 - 1523 }, abstract={Not available.....} } @inproceedings{ieeebib102, title={ Unit commitment using particle swarm optimization combined with Lagrange relaxation}, author = {P. Sriyanyong and Y.H. Song}, booktitle={Power Engineering Society General Meeting, 2005. IEEE}, notes={12-16 June 2005}, year={2005}, pages={2752 - 2759 Vol. 3 }, abstract={This paper proposes particle swarm optimization (PSO) combined with Lagrange relaxation method (LR) for solving unit commitment (UC). The proposed approach employs PSO algorithm for optimal settings of Lagrange multipliers. The feasibility of the pro..... } } @inproceedings{ieeebib1020, title={ Design and Optimization of Self-Biased Complementary Folded Cascode}, author = {V. Ceperic and Z. Butkovic and A. Baric}, booktitle={Electrotechnical Conference, 2006. MELECON 2006. IEEE Mediterranean}, notes={16-19 May 2006}, year={2006}, pages={145 - 148 }, abstract={This paper presents design and optimization procedure of a self-biased complementary folded cascade. A self-biased scheme is chosen as a technique that saves power and circuit area and is less sensitive to process variations. The gain of basic folded.....} } @inproceedings{ieeebib1021, title={ Independent component analysis based filter design for defect detection in low-contrast textured images}, author = {Du-Ming Tsai and Yan-Hsin Tseng and Shin-Min Chao and Chao-Hsuan Yen}, booktitle={18th International Conference on Pattern Recognition, 2006. ICPR 2006. }, notes={Volume 2, 20-24 Aug. 2006}, year={2006}, pages={231 - 234 }, abstract={In this paper, we propose a convolution filtering scheme for detecting defects in low-contrast textured surface images and, especially, focus on the application for glass substrates in Liquid Crystal Display (LCD) manufacturing. A defect embedded in .....} } @inproceedings{ieeebib1022, title={ Dynamic Population Size in PSO-based Multiobjective Optimization}, author = {Wen-Fung Leong and G.G. Yen}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1718 - 1725 }, abstract={Most existing multiobjective particle swarm optimization (MOPSO) designs generally  estimate a fixed population size sufficiently to explore the search space without incurring excessive computational complexity. In this paper, we propos.....} } @inproceedings{ieeebib1023, title={ A Multiresolutional Estimated Gradient Architecture for Global Optimization}, author = {M. Hazen and M.R. Gupta}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={3013 - 3020 }, abstract={In this paper we present a novel optimization algorithm that estimates gradients over regions to search for optima of a non-convex function on both a local and global scale. The proposed architecture is based on three concepts: using the memory of pr.....} } @inproceedings{ieeebib1024, title={ On The Convergence of Information Exchange Methods in Multiple Cooperating Swarms}, author = {M. El-Abd and M.S. Kamel}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1052 - 1056 }, abstract={Different cooperative models have been proposed in the past few years using particle swarm optimization (PSO). These models relied on having more than one swarm running in a parallel or serial fashion while exchanging information among them. The info.....} } @inproceedings{ieeebib1025, title={ The Latest vs. Averaged Recent Experience: Which Better Guides a PSO Algorithm?}, author = {A. Acan and A. Unveren and M. Bodur}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={414 - 419 }, abstract={A particle swarm optimization strategy based on the use of learned experiences averaged over a number of iterations is presented. The personal and the global best solutions over a number of latest iterations are stored and averages of the stored solu.....} } @inproceedings{ieeebib1026, title={ Finding Social Landscapes for PSOs via Kernels}, author = {W.B. Langdon and R. Poli}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1654 - 1661 }, abstract={Particle swarm optimiser and genetic algorithm populations are macro-organisms, which perceive their environment as if filtered via a kernel. The kernel assimilates each individuals sensory abilities so that the collective moves using a greedy.....} } @inproceedings{ieeebib1027, title={ A PSO-based Mobile Sensor Network for Odor Source Localization in Dynamic Environment: Theory, Simulation and Measurement}, author = {W. Jatmiko and K. Sekiyama and T. Fukuda}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1036 - 1043 }, abstract={This paper presents a problem of odor source localization in a dynamic environment, which means the odor distribution is changing over time. Most work on chemical sensing with mobile robots assume an experimental setup that minimizes the influence of.....} } @inproceedings{ieeebib1028, title={ Evolving High-Performance Evolutionary Computations for Space Vehicle Design}, author = {G. Dozier and W. Britt and M.P. SanSoucie and P.V. Hull and M.L. Tinker and R. Unger and S. Bancroft and T. Moeller and D. Rooney}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={2201 - 2207 }, abstract={The Nuclear Electric Vehicle Optimization Toolset (NEVOT) optimizes the design of all major nuclear electric propulsion (NEP) vehicle subsystems for a defined mission within constraints and optimization parameters chosen by a user. The tool currently.....} } @inproceedings{ieeebib1029, title={ A Multi-Agent System-Based Intelligent Heuristic Optimal Control System for A Large-Scale Power Plant}, author = {J.S. Heo and K.Y. Lee}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1544 - 1551 }, abstract={A large-scale power system is required to have a new control system to operate at a higher level of automation, flexibility, robustness, and optimization. In this paper, a Multi-Agent System based Intelligent Heuristic Optimal Control System MAS-IHO.....} } @inproceedings{ieeebib103, title={ Synthesis of antenna array using particle swarm optimization}, author = {T.B. Chen and Y.B. Chen and Y.C. Jiao and E.S. Zhang}, booktitle={Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings}, notes={Volume 3, 4-7 Dec. 2005}, year={2005}, pages={4 pp. }, abstract={The particle swarm optimization algorithm presents a new way to find an optimal solution of a complex optimization problem, where each particle represents a solution to the problem. The particle swarm optimization algorithm can improves the global se..... } } @inproceedings{ieeebib1030, title={ When is a Swarm Necessary?}, author = {T.J. Richer and T.M. Blackwell}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1469 - 1476 }, abstract={This paper compares the performance of particle swarm optimization (PSO) to other optimization algorithms over a continuum of problems. This approach is inspired by state diagrams used in physics. The state space is spanned by the problem parameters,.....} } @inproceedings{ieeebib1031, title={ Multiobjective Multistatic Sonar Sensor Placement}, author = {P.N. Ngatchou and W.L.J. Fox and M.A. El-Sharkawi}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={2713 - 2719 }, abstract={We address the problem of determining the optimal number and placement of multistatic sonar sensors to achieve maximal coverage while minimizing the number of required sensors. The use of a computationally expensive environmentally-dependent acoustic.....} } @inproceedings{ieeebib1032, title={ Medical Data Mining using Particle Swarm Optimization for Temporal Lobe Epilepsy}, author = {M. Ghannad-Rezaie and H. Soltanain-Zadehand and M.-R. Siadat and K.V. Elisevich}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={761 - 768 }, abstract={In clinical problems, numerous factors are usually involved in a medical syndrome. New advances in medicine provide a broad range of diagnosis methods to cover all aspects of a disease. However, huge amounts of raw information may confuse clinicians .....} } @inproceedings{ieeebib1033, title={ A Comparison of Algorithms for the Optimization of Fermentation Processes}, author = {R. Mendes and I. Rocha and E.C. Ferreira and M. Rocha}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={2018 - 2025 }, abstract={The optimization of biotechnological processes is a complex problem that has been intensively studied in the past few years due to the economic impact of the products obtained from fermentations. In fed-batch processes, the goal is to fi nd the optim.....} } @inproceedings{ieeebib1034, title={ Emergent Behaviour, Population-based Search and Low-pass Filtering}, author = {R. Poli and A.H. Wright and N.F. McPhee and W.B. Langdon}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={88 - 95 }, abstract={In recent work we have formulated a model of emergent coordinated behaviour for a population of interacting entities. The model is a modified spring mass model where masses can perceive the environment and generate external forces. As a result of the.....} } @inproceedings{ieeebib1035, title={ Adaptive Resource Reservation Schemes for Multimedia Handoffs in Fourth-Generation Mobile Communications System}, author = {Chenn-Jung Huang and Yi-Ta Chuang and Liang-Chun Chen and Wei Kuang Lai and Yu-Hang Sun}, booktitle={2005 Fifth International Conference on Information, Communications and Signal Processing}, notes={06-09 Dec. 2005}, year={2005}, pages={664 - 668 }, abstract={Many mechanisms based on bandwidth reservation have been proposed in the literature to decrease connection dropping probability for handoffs in cellular communications. The handoff events occur at a much higher rate in packet-switched fourth generati.....} } @inproceedings{ieeebib1036, title={ Neural Network Enhancement of Multiobjective Evolutionary Search}, author = {H. Yapicioglu and G. Dozier and A.E. Smith}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1909 - 1915 }, abstract={In this study, a novel approach is used to identify nondominated solutions to multiobjective optimization problems. The method is composed of a Particle Swarm Optimizer (PSO) coupled with a neural network. The PSO is used to find an initial set of no.....} } @inproceedings{ieeebib1037, title={ Analysis of the Superiority of Parameter Optimization over Genetic Programming for a Difficult Object Detection Problem}, author = {V. Ciesielski and G. Wijesinghe and A. Innes and S. John}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1264 - 1271 }, abstract={We describe a progression of solutions to a di ffi cult object detection problem, that of locating landmarks in X-Rays used in orthodontic treatment planning. In our fi rst formula tion an object detector was a genetic program whose inputs were a num.....} } @inproceedings{ieeebib1038, title={ Human Body Pose Estimation with PSO}, author = {S. Ivekovic and E. Trucco}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1256 - 1263 }, abstract={In this paper we describe the application of Particle Swarm Optimisation to the problem of human body pose estimation from multiple view video sequences. We use a subdivision body model with an underlying skeleton layer to estimate and illustrate the.....} } @inproceedings{ieeebib1039, title={ A Zone Routing Protocol for Bluetooth MANET with Online Adaptive Zone Radius}, author = {Chenn-Jung Huang and Liang-Chun Chen and Yao-Chuan Lin and Yi-Ta Chuang and Wei Kuang Lai and Sheng-Yu Hsiao}, booktitle={2005 Fifth International Conference on Information, Communications and Signal Processing}, notes={06-09 Dec. 2005}, year={2005}, pages={579 - 583 }, abstract={In this paper, a routing protocol that utilizes the characteristics of Bluetooth technology is proposed for Bluetooth-based mobile ad hoc networks. The routing tables are maintained in the master devices and the routing zone radius for each table is .....} } @inproceedings{ieeebib104, title={ Combined algorithm for time-varying system based on improved particle swarm optimization and EWRLS algorithm}, author = {Wei Jian and Yuncan Xue and Qiwen Yang}, booktitle={2005. INDIN '05. 2005 3rd IEEE International Conference on Industrial Informatics}, notes={10-12 Aug. 2005}, year={2005}, pages={562 - 565}, abstract={A combined algorithm based on the improved particle swarm optimization (PSO) and EWRLS algorithm is presented in this paper. A modified particle swarm optimization with velocity disturbance is also presented to enhance the response speed of PSO algor..... } } @inproceedings{ieeebib1040, title={ Dynamic Multi-Swarm Particle Swarm Optimizer with a Novel Constraint-Handling Mechanism}, author = {J.J. Liang and P.N. Suganthan}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={9 - 16 }, abstract={In this paper, a novel constraint-handling mechanism based on multi-swarm is proposed. Different from the existing constraints handling methods, the sub-swarms are adaptively assigned to explore different constraints according to their difficulties. .....} } @inproceedings{ieeebib1041, title={ A Novel Particle Swarm-based Fuzzy Control Scheme}, author = {H.A. Awad}, booktitle={2006 IEEE International Conference on Fuzzy Systems}, notes={July 16-21, 2006}, year={2006}, pages={1939 - 1946}, abstract={Not available.....} } @inproceedings{ieeebib1042, title={ Fuzzy Clustering by Particle Swarm Optimization}, author = {T.A. Runkler and C. Katz}, booktitle={2006 IEEE International Conference on Fuzzy Systems}, notes={July 16-21, 2006}, year={2006}, pages={601 - 608}, abstract={Not available.....} } @inproceedings{ieeebib1043, title={ Fuzzy Modeling Using Chaotic Particle Swarm Approaches Applied to a Yo-yo Motion System}, author = {L. dos Santos Coelho and B. Meirelles Herrera}, booktitle={2006 IEEE International Conference on Fuzzy Systems}, notes={July 16-21, 2006}, year={2006}, pages={2293 - 2298}, abstract={Not available.....} } @inproceedings{ieeebib1044, title={ Multi-objective Particle Swarm Optimization for Fuzzy Logic Based Active Queue Management}, author = {C.N. Nyirenda and D.S. Dawoud}, booktitle={2006 IEEE International Conference on Fuzzy Systems}, notes={July 16-21, 2006}, year={2006}, pages={2231 - 2238}, abstract={Not available.....} } @inproceedings{ieeebib1045, title={ Fitting Fuzzy Membership Functions using Hybrid Particle Swarm Optimization}, author = {A.A.A. Esmin and G. Lambert-Torres}, booktitle={2006 IEEE International Conference on Fuzzy Systems}, notes={July 16-21, 2006}, year={2006}, pages={2112 - 2119}, abstract={Not available.....} } @inproceedings{ieeebib1046, title={ Particle Swarm Optimization-based Fuzzy Predictive Control Strategy}, author = {J. Solis and D. Saez and P.A. Estevez}, booktitle={2006 IEEE International Conference on Fuzzy Systems}, notes={July 16-21, 2006}, year={2006}, pages={1866 - 1871}, abstract={Not available.....} } @inproceedings{ieeebib1047, title={ Optimum Var Sizing \& Allocation Using Particle Swarm Optimization}, author = {A.A. EL-Dib and H.K.M. Youssef and M.M. EL-Metwally and Z. Osman}, booktitle={PES TD 2005/2006}, year={2005/2006}, notes={May 21-24, 2006}, year={2006}, pages={1108 - 1115 }, abstract={Not available.....} } @inproceedings{ieeebib1048, title={ A comparison between the Pittsburgh and Michigan approaches for the binary PSO algorithm}, author = {A. Cervantes and I. Galvan and P. Isasi}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 1, 2-5 Sept. 2005}, pages={290 - 297 Vol.1 }, abstract={This paper shows the performance of the binary PSO algorithm as a classification system. These systems are classified in two different perspectives: the Pittsburgh and the Michigan approaches. In order to implement the Michigan approach binary PSO al.....} } @inproceedings{ieeebib1049, title={ Investigating binary PSO parameter influence on the knights cover problem}, author = {N. Franken and A.P. Engelbrecht}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 1, 2-5 Sept. 2005}, pages={282 - 289 Vol.1 }, abstract={The underlying relationship between various PSO parameters is experimentally examined by applying the binary PSO (BinPSO) algorithm to solve the knights cover problem. An exhaustive analysis of the cognitive and social acceleration constants is perfo.....} } @inproceedings{ieeebib105, title={ Application of particle swarm optimization to the train scheduling for high-speed passenger railroad planning}, author = {Ren Ping and Li Nan and Gao Liqun and Lin Zhiling and Li Yang}, booktitle={IEEE International Symposium on Communications and Information Technology, 2005. ISCIT 2005. }, notes={Volume 1, 12-14 Oct. 2005}, year={2005}, pages={581 - 584 }, abstract={This paper presents an approach for solving the train scheduling for high-speed passenger railroad planning problem through the particle swarm optimization (PSO) for the first time. PSO has demonstrated the ability to deal with non-convex, non-linear..... } } @inproceedings{ieeebib1050, title={ Linear equality constraints and homomorphous mappings in PSO}, author = {C.K. Monson and K.D. Seppi}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 1, 2-5 Sept. 2005}, pages={73 - 80 Vol.1 }, abstract={We present a homomorphous mapping that converts problems with linear equality constraints into fully unconstrained and lower-dimensional problems for optimization with PSO. This approach, in contrast with feasibility preservation methods, allows any .....} } @inproceedings{ieeebib1051, title={ Support Vector Machines with PSO Algorithm for Short-Term Load Forecasting}, author = {Changyin Sun and Dengcai Gong}, booktitle={2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on Networking, Sensing and Control}, notes={23-25 April 2006}, year={2006}, pages={676 - 680}, abstract={Accurate forecasting of short-term electricity load has been one of the most important issues in the electricity industry. Because of the remarkable nonlinear mapping capabilities of forecasting, artificial neural networks have played a crucial role .....} } @inproceedings{ieeebib1052, title={ Parameter identification of induction motor based on particle swarm optimization}, author = {C. Picardi and N. Rogano}, booktitle={International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 2006. SPEEDAM 2006. }, notes={May, 23rd - 26th, 2006}, year={2006}, pages={968 - 973 }, abstract={Not available.....} } @inproceedings{ieeebib1053, title={ Dynamic reconfiguration of reconfigurable manufacturing systems using particle swarm optimization}, author = {Y. Yamada}, booktitle={2006. ICRA 2006. Proceedings 2006 IEEE International Conference on Robotics and Automation}, notes={May 15-19, 2006}, year={2006}, pages={1444 - 1449}, abstract={Not available.....} } @inproceedings{ieeebib1054, title={ A Self-Tuning Analog Proportional-Integral-Derivative (PID) Controller}, author = {V. Aggarwal and Meng Mao and U.-M. O'Reilly}, booktitle={First NASA/ESA Conference on Adaptive Hardware and Systems, 2006. AHS 2006. }, notes={15-18 June 2006}, year={2006}, pages={12 - 19 }, abstract={We present a platform for implementing low power selftuning analog proportional-integral-derivative controllers. By using a model-free tuning method, the platform overcomes problems typically associated with reconfigurable analog arrays. Unlike a sel.....} } @inproceedings{ieeebib1055, title={ Collision detection for deforming linear objects using particle swarm optimization}, author = {Wang Yi and Li Wenhui and Wang Tianzhu and Han Dongfeng and Meng Yu}, booktitle={2006 IEEE International Conference on Granular Computing}, notes={10-12 May 2006}, year={2006}, pages={465 - 468}, abstract={Not available.....} } @inproceedings{ieeebib1056, title={ Quantum-behaved particle swarm optimization based on immune memory and vaccination}, author = {Jing Liu and Jun Sun and W.B. Xu and X.H. Kong}, booktitle={2006 IEEE International Conference on Granular Computing}, notes={10-12 May 2006}, year={2006}, pages={453 - 456}, abstract={Not available.....} } @inproceedings{ieeebib1057, title={ Fuzzy kernel clustering based on particle swarm optimization}, author = {Libiao Zhang and Chunguang Zhou and Ming Ma and Xiaohua Liu and Chunxia Li and Caitang Sun and Miao Liu}, booktitle={2006 IEEE International Conference on Granular Computing}, notes={10-12 May 2006}, year={2006}, pages={428 - 430}, abstract={Not available.....} } @inproceedings{ieeebib1058, title={ Use of Cultural Particle Swarm Optimization for Loneyýs Solenoids Design}, author = {L. dos Santos Coelho and V. Cocco Mariani}, booktitle={2006 12th Biennial IEEE Conference on Electromagnetic Field Computation}, note={2006}, year={2006}, pages={482 - 482 }, abstract={Not available.....} } @inproceedings{ieeebib1059, title={ An Improved Particle Swarm Optimization Method with Application to Multimodal Functions of Inverse Problems}, author = {S.L. Ho and S.Y. Yang and G.Z. Ni and K.F. Wong}, booktitle={2006 12th Biennial IEEE Conference on Electromagnetic Field Computation}, note={2006}, year={2006}, pages={125 - 125 }, abstract={Not available.....} } @inproceedings{ieeebib106, title={ Multiuser detection employing particle swarm optimization in space-time CDMA systems}, author = {Ying Zhao and Junli Zheng}, booktitle={IEEE International Symposium on Communications and Information Technology, 2005. ISCIT 2005. }, notes={Volume 2, 12-14 Oct. 2005}, year={2005}, pages={972 - 974 }, abstract={This paper is focused on the problem of multiuser detection (MUD) using the modified particle swarm optimization (PSO) algorithm for direct-sequence code-division multiple-access (DS-CDMA) systems with space-time block codes (STBC). This novel approa..... } } @inproceedings{ieeebib1060, title={ Evolutionary Algorithms with Particle Swarm Movements}, author = {V. Miranda}, booktitle={Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, 2005. }, notes={6-10 Nov. 2005}, year={2005}, pages={6 - 21 }, abstract={Not available.....} } @inproceedings{ieeebib1061, title={ White Blood Cell Image Segmentation Using On-line Trained Neural Network}, author = {Fang Yi and Zheng Chongxun and Pan Chen and Liu Li}, booktitle={Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the}, notes={01-04 Sept. 2005}, year={2005}, pages={6476 - 6479 }, abstract={This paper addresses a fast white blood cell (WBC) image segmentation scheme implemented by on-line trained neural network. A pre-selecting technique, based on mean shift algorithm and uniform sampling, is utilized as an initialization tool to largel.....} } @inproceedings{ieeebib1062, title={ Genetical Swarm Optimization: a New Hybrid Evolutionary Algorithm for Electromagnetic Applications}, author = {E.A. Grimaldi and F. Grimaccia and M. Mussetta and P. Pirinoli and R.E. Zich}, booktitle={18th International Conference on Applied Electromagnetics and Communications, 2005. ICECom 2005. }, notes={12-14 Oct. 2005}, year={2005}, pages={1 - 4 }, abstract={In this paper a new effective optimization algorithm suitably developed for electromagnetic applications called Genetical Swarm Optimization (GSO) will be presented. This is an hybrid algorithm developed in order to combine in the most effective way .....} } @inproceedings{ieeebib1063, title={ Particle Swarn Optimization with Fast Local Search for the Blind Traveling Salesman Problem}, author = {H.S. Lope and L.S. Coelho}, booktitle={Fifth International Conference on Hybrid Intelligent Systems, 2005. }, notes={6-9 Nov. 2005}, year={2005}, pages={245 - 250 }, abstract={The classical travelling salesman problem (TSP) is to determine a tour in a weighted graph (that is, a cycle that visits every vertex exactly once) such that the sum of the weights of the edges in this tour is minimal. Hybrid methods, based on nature.....} } @inproceedings{ieeebib1064, title={ Analysis of MALDI-TOF Serum Profiles for Biomarker Selection and Sample Classification}, author = {H.W. Ressom and R.S. Varghese and E. Orvisky and S.K. Drake and G.L. Hortin and M. Abdel-Hamid and C.A. Loffredo and R. Goldman}, booktitle={Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2005. CIBCB '05. }, notes={14-15 Nov. 2005}, year={2005}, pages={1 - 7 }, abstract={Mass spectrometric profiles of peptides and proteins obtained by current technologies are characterized by complex spectra, high dimensionality, and substantial noise. These characteristics generate challenges in discovery of proteins and protein-pro.....} } @inproceedings{ieeebib1065, title={ Improved particle swam optimization algorithm for OPF problems}, author = {B. Zhao and C.X. Guo and Y.J. Cao}, booktitle={Power Systems Conference and Exposition, 2004. IEEE PES}, notes={10-13 Oct. 2004}, year={2004}, pages={233 - 238 vol.1 }, abstract={This work presents the solution of the optimal power flow (OPF) using particle swarm optimization (PSO) technique. The main goal of this paper is to verify the viability of using PSO problem composed by the different objective functions. Incorporatio.....} } @inproceedings{ieeebib1066, title={ A Hybrid Intelligent QoS Multicast Routing Algorithm in NGI}, author = {Junwei Wang and Xingwei Wang and Min Huang}, booktitle={Sixth International Conference on Parallel and Distributed Computing, Applications and Technologies, 2005. PDCAT 2005. }, notes={05-08 Dec. 2005}, year={2005}, pages={723 - 727 }, abstract={Taking the characteristics of multi-constrained QoS (Quality of Service) routing in NGI (Next Generation Internet) into account, a hybrid intelligent multicast QoS routing algorithm based on PSO (Particle Swarm Optimization) and GA (Genetic Algorithm.....)} } @inproceedings{ieeebib1067, title={ Comparison of Artificial Life Techniques for Market Simulation}, author = {Feng Gao and G. Gutierrez-Alcaraz and G.B. Sheble}, booktitle={Proceedings of the 39th Annual Hawaii International Conference on System Sciences, 2006. HICSS '06. }, notes={Volume 10, 04-07 Jan. 2006}, year={2006}, pages={243a - 243a }, abstract={Electricity industries worldwide are undergoing a period of profound upheaval. Conventional vertically integrated mechanism is replaced by a competitive market environment. A pure operating cost optimization is not enough to model the distributed, la.....} } @inproceedings{ieeebib1068, title={ PSO under an adaptive scheme}, author = {M. Breaban and H. Luchian}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 2, 2-5 Sept. 2005}, pages={1212 - 1217 Vol. 2 }, abstract={This paper presents an attempt to transform PSO into a self-adaptive algorithm based on specific swarm-inspired operators. New features are introduced: spatial expansion intended to overcome premature convergence an algorithm called improved PSO, IP.....} } @inproceedings{ieeebib1069, title={ A hybrid particle swarm/ant colony algorithm for the classification of hierarchical biological data}, author = {N. Holden and A.A. Freitas}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={100 - 107}, abstract={This paper proposes a hybrid PSO/ACO algorithm for hierarchical classification, where the classes to be predicted are arranged in a tree-like hierarchy. The performance of the algorithm is evaluated on a challenging biological data set, involving the.....} } @inproceedings{ieeebib107, title={ Dynamic clustering using support vector learning with particle swarm optimization}, author = {Jiann-Horng Lin and Ting-Yu Cheng}, booktitle={18th International Conference on Systems Engineering, 2005. ICSEng 2005. }, notes={16-18 Aug. 2005}, year={2005}, pages={218 - 223 }, abstract={This paper presents a new approach to the support vector learning for dynamic clustering based on particle swarm optimization. Support vector clustering requires solving a constrained quadratic optimization problem. This problem often involves a matr..... } } @inproceedings{ieeebib1070, title={ A Swarm-Based Volition/Attention Framework for Object Recognition}, author = {Y. Owechko and S. Medasani}, booktitle={2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition}, notes={Volume 3, 20-26 June 2005}, year={2005}, pages={91 - 91 }, abstract={Visual attention helps identify the salient parts of a scene and enables efficient object recognition by allocating visual resources to more relevant regions of the scene. In this paper, we present an object recognition framework that combines top-do.....} } @inproceedings{ieeebib1071, title={ Multi-View Classifier Swarms for Pedestrian Detection and Tracking}, author = {P. Saisan and S. Medasani and Y. Owechko}, booktitle={2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition}, notes={Volume 3, 20-26 June 2005}, year={2005}, pages={18 - 18 }, abstract={We describe a novel method for recognition and localization of objects in 3D space using multiple views. We pose the task of classifying and locating objects in 3D space as an optimization problem that combines 2D classifier scores from two separate .....} } @inproceedings{ieeebib1072, title={ Fixed Channel Assignment in Cellular Radio Networks Using Particle Swarm Optimization}, author = {Yangyang Zhang and D.C. O'Brien}, booktitle={Proceedings of the IEEE International Symposium on Industrial Electronics, 2005. ISIE 2005. }, notes={Volume 4, June 20-23, 2005}, year={2005}, pages={1751 - 1756 }, abstract={Not available.....} } @inproceedings{ieeebib1073, title={ Particle swarm optimization and its applications to VLSI design and video technology}, author = {R. Eberhart and Yuhui Shi}, booktitle={Proceedings of 2005 IEEE International Workshop on VLSI Design and Video Technology, 2005. }, notes={28-30 May 2005}, year={2005}, pages={xxiii - xxiii }, abstract={Not available.....} } @inproceedings{ieeebib1074, title={ Design of yagi-uda antenna and electromagnetically coupled curl antenna using particle swarm optimization algorithm}, author = {S.H. Zainud-Deen and K.R. Mahmoud and M. El-Adawy and S.M.M. Ibrahem}, booktitle={Radio Science Conference, 2005. NRSC 2005. Proceedings of the Twenty-Second National}, notes={March 15-17, 2005}, year={2005}, pages={115 - 124 }, abstract={Not available.....} } @inproceedings{ieeebib1075, title={ Analogue filter tuning for antenna matching with multiple objective particle swarm optimization}, author = {Yangyang Zhang and W.Q. Malik}, booktitle={2005 IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication}, notes={April 18-19, 2005}, year={2005}, pages={196 - 198 }, abstract={Not available.....} } @inproceedings{ieeebib1076, title={ Simulating an indoor ultra wideband channel based on a niching particle swarm optimizer}, author = {Yifan Chen and V.K. Dubey}, booktitle={2005 IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication}, notes={April 18-19, 2005}, year={2005}, pages={57 - 60 }, abstract={Not available.....} } @inproceedings{ieeebib1077, title={ A modified particle swarm algorithm for robotic mapping of hazardous environments}, author = {C.T. Hardin and X. Cui and R.K. Ragade and J.H. Graham and A.S. Elmaghraby}, booktitle={World Automation Congress, 2004. Proceedings}, notes={Volume 17, 28 June - 1 July 2004}, year={2004}, pages={31 - 36 }, abstract={Not available.....} } @inproceedings{ieeebib1078, title={ A novel multiobjective particle swarm optimization for buoys-arrangement design}, author = {Yongde Zhang and Shabai Huang}, booktitle={Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004)}, notes={2004}, year={2004}, pages={24 - 30 }, abstract={Not available.....} } @inproceedings{ieeebib1079, title={ A new discrete binary particle swarm optimization based on learning automata}, author = {R. Rastegar and M.R. Meybodi and K. Badie}, booktitle={Proceedings of the 2004 International Conference on Machine Learning and Applications, 2004. }, notes={16-18 December, 2004}, year={2004}, pages={456 - 462 }, abstract={Not available.....} } @inproceedings{ieeebib108, title={ A new particle swarm optimization technique}, author = {Chunming Yang and D. Simon}, booktitle={18th International Conference on Systems Engineering, 2005. ICSEng 2005. }, notes={16-18 Aug. 2005}, year={2005}, pages={164 - 169 }, abstract={In this paper, a new particle swarm optimization method (NPSO) is proposed. It is compared with the regular particle swarm optimizer (PSO) invented by Kennedy and Eberhart in 1995 based on four different benchmark functions. PSO is motivated by the s..... } } @inproceedings{ieeebib1080, title={ Classifier Swarms for Human Detection in Infrared Imagery}, author = {Y. Owechko and S. Medasani and N. Srinivasa}, booktitle={2004 Conference on Computer Vision and Pattern Recognition Workshop}, notes={27-02 June 2004}, year={2004}, pages={121 - 121 }, abstract={In this paper, we describe a new method for visual recognition of objects in an image that combines feature-based object classification with efficient search mechanisms based on swarm intelligence. Our approach utilizes the particle swarm optimizatio.....} } @inproceedings{ieeebib1081, title={ Load flow solution using hybrid particle swarm optimization}, author = {A.A. EL-Dib and H.K.M. Youssef and M.M. EL-Metwally and Z. Osman}, booktitle={2004 International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04. }, notes={5-7 Sept. 2004}, year={2004}, pages={742 - 746 }, abstract={Not available.....} } @inproceedings{ieeebib1082, title={ A modified particle swarm optimizer applied to the solution of the economic dispatch problem}, author = {S.F. Mekhamer and Y.G. Moustafa and N. EI-Sherif and M.M. Mansour}, booktitle={2004 International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04. }, notes={5-7 Sept. 2004}, year={2004}, pages={725 - 731 }, abstract={Not available.....} } @inproceedings{ieeebib1083, title={ Optimal placement of wavelength converters in WDM networks using particle swarm optimizer}, author = {Choon Fang Teo and Yun Cie Foo and Su Fong Chien and A.L.Y. Low and B. Venkatesh and A.H. You}, booktitle={2004 IEEE International Conference on Communications}, notes={Volume 3, 20-24 June 2004}, year={2004}, pages={1669 - 1673}, abstract={Not available.....} } @inproceedings{ieeebib1084, title={ Optimization of a Spline-Shaped UWB Antenna by PSO}, author = { L. Lizzi and F. Viani and R. Azaro and A. Massa}, booktitle={IEEE Antennas and Wireless Propagation Letters : Accepted for future publication}, notes={Volume PP, Issue 99, 2007}, year={2007}, pages={1 - 1 }, abstract={This letter presents the design of a planar antenna for UWB applications with a bandwidth of 5.5 GHz over 3.7 to 9.2 GHz and return loss values lower than -10 dB . The antenna geometry is described in terms of a spline-based representation whose cont..... } } @article{ieeebibJ1085, title={ Benchmark Antenna Problems for Evolutionary Optimization Algorithms}, author={Mario Fernndez Pantoja and Amelia Rubio Bretones and Rafael Gmez Martin}, journal={IEEE Transactions on Antennas and Propagation}, volume= 55, issue= 4, date={ April 2007}, pages={1111 - 1121 }, year={2007}, abstract={ A set of antenna-optimization problems is presented that satisfies the necessary requirements to form a test suite useful for measuring and comparing the performance of different evolutionary optimization algorithms (EAs) when they are applied.....} } @article{ieeebibJ1086, title={ Optimized design of a multifunction/multiband antenna for automotive rescue systems}, author={R. Azaro and F.G.B. De Natale and M. Donelli and A. Massa and E. Zeni}, journal={IEEE Transactions on Antennas and Propagation}, volume= 54, issue= 2, date={}, part1={ Feb. 2006 Page(s):392 - 400 }, year={2006}, abstract={The development of efficient automotive accident management systems requires the design of complex multifunction antennas enabling different wireless services (e.g., localization, voice and data communications, emergency calls, etc.). Starting from d.....} } @inproceedings{ieeebib1087, title={ Speed Control of Three-inertia Systems by Full-order Controllers}, author = {Y. Matsui}, booktitle={SICE-ICASE, 2006. International Joint Conference}, notes={Oct. 2006}, year={2006}, pages={4366 - 4369 }, abstract={This paper proposes a design method of controllers for three-inertia systems. The controllers designed by the method are compared to the PID controllers. The validity of the method is confirmed by the simulations......} } @inproceedings{ieeebib1088, title={ Performance Optimization of Wireless Video Sensor Networks using Swarm Optimization with Convex Mapping}, author = {Bo Wang and Zhihai He}, booktitle={2006 IEEE International Conference on Image Processing}, notes={Oct. 2006}, year={2006}, pages={1293 - 1296}, abstract={A wireless video sensor network (WVSN) is a system of spatially distributed video sensors which capture, process and transmit video information over a wireless ad hoc network. The performance optimization in WVSN is a nonlinear high-dimension constra.....} } @inproceedings{ieeebib1089, title={ An effective hybrid optimization algorithm for the flow shop scheduling problem}, author = {Sun Kai and Yang Genke}, booktitle={2006 IEEE International Conference on Information Acquisition}, notes={Aug. 2006}, year={2006}, pages={1234 - 1238}, abstract={This paper presents a new multi-swarm co-evolutionary algorithm named parallel particle swam optimization (PPSO) on the basis of standard PSO algorithm. Simulated annealing (SA) algorithm was introduced to increase escaping probability from local opt.....} } @inproceedings{ieeebib109, title={ Particle swarm optimization and fitness sharing to solve multi-objective optimization problems}, author = {M. Salazar-Lechuga and J.E. Rowe}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 2, 2-5 Sept. 2005}, pages={1204 - 1211 Vol. 2 }, abstract={The particle swarm optimization algorithm has been shown to be a competitive heuristic to solve multi-objective optimization problems. Also, fitness sharing concepts have shown to be significant when used by multi-objective optimization methods. In t..... } } @inproceedings{ieeebib1090, title={ Integration of IGCC Plants and Reachable Multi-Objective ThermoEconomic Optimization}, author = {Zhengmao Ye and H.P. Mohamadian and Yongmao Ye}, booktitle={2006 IEEE International Conference on Computational Cybernetics}, notes={Aug. 2006}, year={2006}, pages={1 - 3}, abstract={The gasification process of IGCC plants enables the production of electricity as main product and production of heat and some chemicals (e.g., sulfur, slag) as by-products. In order to testify its feasibility for large scale production, IGCC control .....} } @inproceedings{ieeebib1091, title={ BP neural network optimized with PSO algorithm and its application in forecasting}, author = {Wen Guo and Yizheng Qiao and Haiyan Hou}, booktitle={2006 IEEE International Conference on Information Acquisition}, notes={Aug. 2006}, year={2006}, pages={617 - 621}, abstract={An approach that neural network optimized with PSO algorithm is proposed in the paper. Unlike conventional training method with gradient descent method only, this paper introduces a hybrid training algorithm by combining the PSO and BP algorithm. The.....} } @inproceedings{ieeebib1092, title={ Hierarchical Routing in Traffic Using Swarm-Intelligence}, author = {B. Tatomir and L. Rothkrantz}, booktitle={Proceedings of IEEE Intelligent Transportation Systems, 2006. }, notes={2006}, year={2006}, pages={230 - 235 }, abstract={In this paper the design of a dynamic routing system, called hierarchical routing system, is presented. It splits traffic networks into several smaller and less complex networks by introducing a hierarchy between the roads. An algorithm inspired from.....} } @inproceedings{ieeebib1093, title={ Meta Heuristic Search Algorithms for Short-Term Hydrothermal Scheduling}, author = {N. Sinha and Loi-Lei Lai}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={4050 - 4056 }, abstract={This paper presents the performances of meta heuristic search algorithms in solving short-term hydro thermal scheduling problems. Meta heuristic search algorithms like GA, CEP, FEP, IFEP and PSO have been developed for hydrothermal scheduling problem.....} } @inproceedings{ieeebib1094, title={ A Novel Adaptive PMD Compensation System Based on PSO Algorithm}, author = {Ying Chen and Qi-Guang Zhu}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={344 - 349 }, abstract={An adaptive PMD compensation system used in WDM telecommunication network has been proposed, in which a polarization scrambler was combined with orthogonal polarization splitting detection to achieve multi-channel degree of polarization (DOP) detecti.....} } @inproceedings{ieeebib1095, title={ Short-Term Electric Load Forecasting Based on SAPSO-ANN Algorithm}, author = {Xiang Li and Shang-Dong Yang and Jian-Xun Qi and Shu-Xia Yang}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={2882 - 2885 }, abstract={For the economical, secure and stable operation of the electric power system, the short-term load forecasting plays a vital role. The paper applies the SAPSO-ANN model to forecast the short-term electric load. In order to enhance the generality of th.....} } @inproceedings{ieeebib1096, title={ On learning performance evaluation for some psycho-learning experimental work versus an optimal swarm intelligent system}, author = {H.M. Hassan}, booktitle={Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, 2005. }, notes={18-21 Dec. 2005}, year={2005}, pages={658 - 664 }, abstract={Some models closely related to animal psycho-learning, and a swarm intelligent system, are comparatively presented. More specifically, three introduced models are inspired by creatures' behavioral learning phenomenon, observed in nature. Two of prese.....} } @inproceedings{ieeebib1097, title={ A fault-tolerant P-Q decoupled control scheme for static synchronous series compensator}, author = {Wei Qiao and R.G. Harley and G.K. Venayagamoorthy}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={8 pp. }, abstract={Control of nonlinear devices in power systems relies on the availability and the quality of sensor measurements. Measurements can be corrupted or interrupted due to sensor failure, broken or bad connections, bad communication, or malfunction of some .....} } @inproceedings{ieeebib1098, title={ A nature inspired multi-agent framework for autonomic service management in ubiquitous computing environments}, author = {F. Chiang and R. Braun}, booktitle={2005 ICSC Congress on Computational Intelligence Methods and Applications}, notes={15-17 Dec. 2005}, year={2005}, pages={5 pp. }, abstract={This paper describes the design of a scalable biomimetic framework that addresses several key issues of autonomous agents in the management domain of complex ubiquitous service-oriented networks. We propose an autonomous network service management pl.....} } @inproceedings{ieeebib1099, title={ Theoretical foundations for multiple rendezvous of glowworm-inspired mobile agents with variable local-decision domains}, author = {K.N. Krishnanand and D. Ghose}, booktitle={American Control Conference, 2006}, year={2006}, notes={14-16 June 2006}, pages={6 pp. }, abstract={We present the theoretical foundations for the multiple rendezvous problem involving design of local control strategies that enable groups of visibility-limited mobile agents to split into subgroups, exhibit simultaneous taxis behavior towards, and e.....} } @inproceedings{ieeebib11, title={ A modified adaptive particle swarm optimization algorithm}, author = {Wang Lei and Kang Qi and Xiao Hui and Wu Qidi}, booktitle={2005. ICIT 2005. IEEE International Conference on Industrial Technology}, notes={14-17 Dec. 2005}, year={2005}, pages={209 - 214}, abstract={It is effective to avoid falling into local optimums at the original stage of the computation that the knowledge of multi-optimum distribution state is introduced into general programming of the particle swarm movement in particle swarm optimization...... } } @inproceedings{ieeebib110, title={ Particle swarm optimization for unsupervised robotic learning}, author = {J. Pugh and A. Martinoli and Y. Zhang}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={92 - 99}, abstract={We explore using particle swarm optimization on problems with noisy performance evaluation, focusing on unsupervised robotic learning. We adapt a technique of overcoming noise used in genetic algorithms for use with particle swarm optimization, and e..... } } @inproceedings{ieeebib1100, title={ Emergence-oriented programming}, author = {D.W. Palmer and M. Kirschenbaum and L. Seiter}, booktitle={2005 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 2, 10-12 Oct. 2005}, year={2005}, pages={1441 - 1448 Vol. 2}, abstract={In this paper we describe emergence-oriented programming (EOP), a novel, human-centric technique to engineer swarm algorithms at a higher level of complexity than those developed with simple reactive agents. The process is iterative, building modules.....} } @inproceedings{ieeebib1102, title={ Extending the shortest-path swarm algorithm to cycle detection}, author = {K. Berridge and J. Seitzer}, booktitle={48th Midwest Symposium on Circuits and Systems, 2005. }, notes={7-10 Aug. 2005}, year={2005}, pages={931 - 934 Vol. 2}, abstract={Swarm programming is a method that uses many simple agents to collectively perform a complex task. The approach is based on the emergent behavior of a swarm of simple agents as they interact with each other and the environment. The swarming algorithm.....} } @inproceedings{ieeebib1104, title={ An ant colony optimization model for wireless ad-hoc network autoconfiguration}, author = {V. Kumar and E. Cole}, booktitle={2005 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 1, 10-12 Oct. 2005}, year={2005}, pages={103 - 108 Vol. 1}, abstract={The dynamic host configuration protocol (DHCP) has been a commonly employed technique to distribute IP addresses on networks where static address allocation may not be appropriate. DHCP is normally feasible on networks that are client-server based as.....} } @inproceedings{ieeebib1105, title={ Swarm based logistics supply structure evolving simulation for strategic decision}, author = {Gang Xiao and Bao Xi}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005. }, notes={Volume 6, 18-21 Aug. 2005}, year={2005}, pages={3624 - 3628 Vol. 6 }, abstract={Corporation's strategic decision in logistics demand and supply management affects all aspects about profit advantage in the increasingly competitive market. This research studies how the long-term logistics strategic decision impacts on all factors .....} } @inproceedings{ieeebib1106, title={ Constraint handling and stochastic ranking in ACO}, author = {B. Meyer}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 3, 2-5 Sept. 2005}, pages={2683 - 2690 Vol. 3 }, abstract={Many industrial and academic optimization problems have successfully been tackled with ant colony optimization (ACO), but the ability of ACO to deal with hard constraints has not yet been investigated widely. Most real-world applications, such as fle.....} } @inproceedings{ieeebib1107, title={ Finding attack strategies for predator swarms using genetic algorithms}, author = {R.E. Leigh and T. Morelli and S.J. Louis and M. Nicolescu and C. Miles}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 3, 2-5 Sept. 2005}, pages={2422 - 2428 Vol. 3 }, abstract={Behavior based architectures have many parameters that must be tuned to produce effective and believable agents. The authors used genetic algorithms to tune simple behavior based controllers for predators and prey. First, the predator tries to maximi.....} } @inproceedings{ieeebib1108, title={ Data clustering by ant colony on a digraph}, author = {Ling Chen and Li Tu and Hong-Jian Chen}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005. }, notes={Volume 3, 18-21 Aug. 2005}, year={2005}, pages={1686 - 1692 Vol. 3 }, abstract={An adaptive data clustering algorithm based on ant colony (ant-cluster) is presented. Enlightened by the self-organizing behavior of ant society, we assign acceptance rates on the directed edges of a pheromone digraph in ant-cluster system. The phero.....} } @inproceedings{ieeebib1109, title={ Missing sensors restoration for system control and diagnostics}, author = {M.A. Ei-Sharkawi and R.J. Marks II }, booktitle={4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, 2003. SDEMPED 2003. }, notes={24-26 Aug. 2003}, year={2003}, pages={338 - 341 }, abstract={Error free measurements are an essential requirement for system monitoring, diagnosis, and control. Measurements can be corrupted or interrupted due to sensor failure, broken links, or bad communication. Control, monitoring and diagnostics cannot ope.....} } @inproceedings{ieeebib111, title={ Perceptive particle swarm optimisation: an investigation}, author = {B. Kaewkamnerdpong and P.J. Bentley}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={169 - 176}, abstract={Conventional particle swarm optimisation relies on exchanging information through social interaction among individuals. However for real-world problems involving control of physical agents (i.e., robot control), such detailed social interaction is no..... } } @inproceedings{ieeebib1110, title={ An ACO algorithm for service restoration in power distribution systems}, author = {I. Watanabe}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 3, 2-5 Sept. 2005}, pages={2864 - 2871 Vol. 3 }, abstract={Service restoration in power distribution systems involves operating the line switches to restore as many loads as possible for the areas isolated by a fault. In service restoration, not only the final network configuration but also the sequence of s.....} } @inproceedings{ieeebib1111, title={ Swarm intelligence in automated electrical wafer sort classification}, author = {E. Miguelanez and A.M.S. Zalzala and P. Buxton}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 2, 2-5 Sept. 2005}, pages={1597 - 1604 Vol. 2 }, abstract={The semiconductor manufacturing domain is by no doubt a rich and challenging environment for the application of machine learning. Some of the demanding characteristic of semiconductor data include high dimensionality, mixtures of categorical and nume.....} } @inproceedings{ieeebib1112, title={ Dealing with noise in ant-based clustering}, author = {D. Zaharie and F. Zamfirache}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 3, 2-5 Sept. 2005}, pages={2395 - 2401 Vol. 3 }, abstract={Separating the noise from data in a clustering process is an important issue in practical applications. Various algorithms, most of them based on density functions approaches, have been developed lately. The aim of this work is to analyze the ability.....} } @inproceedings{ieeebib1113, title={ Evolving swarms that build 3D structures}, author = {S. von Mammen and C. Jacob and G. Kokai}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 2, 2-5 Sept. 2005}, pages={1434 - 1441 Vol. 2 }, abstract={The complex interactions of natural swarms, for example formed by some social insects, are difficult to comprehend. Considering tasks such as nest-building, the necessary underlying communication presumably happens indirectly by changing and reacting.....} } @inproceedings{ieeebib1114, title={ SWARM-BOT: an experiment in swarm robotics}, author = {M. Dorigo}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={192 - 200}, abstract={This paper provides an overview of the SWARM-BOTS project, a robotics project sponsored by the Future and Emerging Technologies program of the European Commission (IST-2000-31010). We describe the s-bot, a small autonomous robot with self-assembling .....} } @inproceedings{ieeebib1115, title={ Information exchange in multiple cooperating swarms}, author = {M. El-Abd and M. Kamel}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={138 - 142}, abstract={This paper investigates the idea of having two cooperating swarms exchanging information in order to solve an optimization problem. The information being exchanged between the two swarms is an important factor that affects the quality of the obtained.....} } @inproceedings{ieeebib1116, title={ Swarm intelligence for routing in mobile ad hoc networks}, author = {G. Di Caro and F. Ducatelle and L.M. Gambardella}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={76 - 83}, abstract={Mobile ad hoc networks are communication networks built up of a collection of mobile devices, which can communicate through wireless connections. Routing is the task of directing data packets from a source node to a given destination. This task is pa.....} } @inproceedings{ieeebib1117, title={ Swarm approach for a connectivity problem in wireless networks}, author = {R. Montemanni and L.M. Gambardella}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={265 - 272}, abstract={We consider the problem of assigning transmission powers to the nodes of a wireless network in such a way that all the nodes are connected by bidirectional links and the total power consumption is minimized. Since no central authority with a global .....} } @inproceedings{ieeebib1118, title={ Facility layout using swarm intelligence}, author = {C.T. Hardin and J.S. Usher}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={424 - 427}, abstract={Facility layout problems are intriguing combinatorial problems that involve determining the location and shape of various departments in a facility based upon inter-department volume and distance measures. We propose a method that divides a facility .....} } @inproceedings{ieeebib1119, title={ Designing decentralized software for a wireless network environment: evaluating patterns of mobility for a mobile agent swarm}, author = {V.A. Cicirello and A. Mroczkowski and W. Regli}, booktitle={2005 IEEE 2nd Symposium on Multi-Agent Security and Survivability}, notes={30-31 Aug. 2005}, year={2005}, pages={49 - 57 }, abstract={Designing decentralized software applications for a wireless network environment offers harsh challenges to the software engineer. All of the usual difficulties associated with a distributed system are present, but are amplified by the inherent dynam.....} } @inproceedings{ieeebib112, title={ Fuzzy discrete particle swarm optimization for solving traveling salesman problem}, author = {Wei Pang and Kang-ping Wang and Chun-guang Zhou and Long-jiang Dong}, booktitle={The Fourth International Conference on Computer and Information Technology, 2004. CIT '04. }, notes={14-16 Sept. 2004}, year={2004}, pages={796 - 800 }, abstract={Particle swarm optimization, as an evolutionary computing technique, has succeeded in many continuous problems, but research on discrete problems especially combinatorial optimization problem has been done little according to Kennedy and Eberhart (19..... )} } @inproceedings{ieeebib1122, title={ Inference of genetic regulatory networks with recurrent neural network models}, author = {Rui Xu and Xiao Hu and D.C. Wunsch, II}, booktitle={Engineering in Medicine and Biology Society, 2004. EMBC 2004. Conference Proceedings. 26th Annual International Conference of the}, notes={Volume 2, 2004}, year={2004}, pages={2905 - 2908 Vol.4 }, abstract={Large-scale gene expression data coming from microarray experiments provide us a new means to reveal fundamental cellular processes, investigate functions of genes, and understand relations and interactions among them. To infer genetic regulatory net.....} } @inproceedings{ieeebib1124, title={ Nonlinear blind source separation using coherence function}, author = {T. Oku and A. Sano}, booktitle={SICE 2003 Annual Conference}, notes={Volume 3, 4-6 Aug. 2003}, year={2003}, pages={2550 - 2560 Vol.3 }, abstract={This paper is concerned with blind source separation (BSS) in which the source signals are instantaneously mixed in unknown linear and nonlinear processes. A coherent function is introduced to the criterion for BSS as well as mutual information to co.....} } @inproceedings{ieeebib1125, title={ Hybrid evolutionary algorithms based on PSO and GA}, author = {X.H. Shi and Y.H. Lu and C.G. Zhou and H.P. Lee and W.Z. Lin and Y.C. Liang}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03. }, notes={Volume 4, 8-12 Dec. 2003}, year={2003}, pages={2393 - 2399 Vol.4 }, abstract={Inspired by the idea of genetic algorithm, we propose two hybrid evolutionary algorithms based on PSO and GA methods through crossing over the PSO and GA algorithms. The main ideas of the two proposed methods are to integrate PSO and GA methods in pa.....} } @inproceedings{ieeebib1126, title={ Cultural swarms: knowledge-driven problem solving in social systems}, author = {R.G. Reynolds and B. Peng and J.J. Brewster}, booktitle={2003. IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 4, 5-8 Oct. 2003}, year={2003}, pages={3589 - 3594 vol.4}, abstract={In this paper we investigate how diverse knowledge sources interact to direct individuals in a swarm population. We identify three basic phases of problem solving that are generated by the swarm population in the solution of real valued function opti.....} } @inproceedings{ieeebib1128, title={Immune, swarm, and evolutionary algorithms. Part I: basic models}, author={L.N. de Castro}, bootktitle={Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02. }, notes={Volume 3, 18-22 Nov. 2002}, year={2002}, pages={1464 - 1468 vol.3 }, abstract={These two papers have three main aims. First (Part I), to review the general algorithms of immune, swarm and evolutionary systems. Second (Part II), to present a philosophical discussion about the similarities and differences between these paradigms,.....} } @inproceedings{ieeebib1129, title={ Swarm directions embedded in fast evolutionary programming}, author = {Chengjian Wei and Zhenya He and Yifeng Zhang and Wenjiang Pei}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02. }, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1278 - 1283 }, abstract={Evolutionary programming has been applied to many optimization problems. However, on some function optimization problems its convergence rate is slow. In this paper, swarm directions are embedded in fast evolutionary programming. The swarm direction .....} } @inproceedings{ieeebib113, title={ Neural networks learning using vbest model particle swarm optimisation}, author = {Hong-Bo Liu and Yi-Yuan Tang and Jun Meng and Ye Ji}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004. }, notes={Volume 5, 26-29 Aug. 2004}, year={2004}, pages={3157 - 3159 vol.5 }, abstract={The two most commonly used methods are known as gbest model and lbest model in particle swarm optimization (PSO). The gbest model converges quickly on problem solutions but has a weakness of becoming trapped in local optima, while the lbest model is ..... } } @inproceedings{ieeebib1130, title={ PSO-Based Real-Time Control of Planar Uniform Circular Arrays}, author = { M. Benedetti and R. Azaro and D. Franceschini and A. Massa}, booktitle={IEEE Antennas and Wireless Propagation Letters : Accepted for future publication}, notes={Volume PP, Issue 99, 2006}, year={2006}, pages={1 - 1 }, abstract={This paper is aimed at assessing the effectiveness of the phase-only control strategy based on a customized PSO when applied to planar uniform circular arrays (PUCA) and in the presence of interferences both in the near-field and far-field of the ant..... } } @inproceedings{ieeebib114, title={ A quantum particle swarm optimization}, author = {Shuyuan Yang and Min Wang and Licheng jiao}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004. }, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={320 - 324 Vol.1 }, abstract={The particle swarm optimization algorithm is a new methodology in evolutionary computation. It has been found to be extremely effective is solving a wide range of engineering problems, however, it is of low efficiency in dealing with the discrete pro..... } } @inproceedings{ieeebib115, title={ Training feedforward neural networks using multi-phase particle swarm optimization}, author = {B. Al-kazemi and C.K. Mohan}, booktitle={Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02. }, notes={Volume 5, 18-22 Nov. 2002}, year={2002}, pages={2615 - 2619 vol.5 }, abstract={The multi-phase particle swarm optimization algorithm (MPPSO) is a variant of the particle swarm optimization algorithm. It simultaneously evolves multiple groups of particles that change their search criterion when changing the phases, and also inco..... } } @article{ieeebibJ116, title={ Advances in Particle Swarm Optimization for Antenna Designs: Real-Number, Binary, Single-Objective and Multiobjective Implementations}, author={Nanbo Jin and Yahya Rahmat-Samii}, journal={IEEE Transactions on Antennas and Propagation}, volume= 55, issue= 3, date={}, part1={ March 2007 Page(s):556 - 567 }, year=2007, abstract={The particle swarm optimization (PSO) is a recently developed evolutionary algorithm (EA) based on the swarm behavior in the nature. This paper presents recent advances in applying a versatile PSO engine to real-number, binary, single-objective and m..... } } @article{ieeebibJ117, title={ Boundary Conditions in Particle Swarm Optimization Revisited}, author={Shenheng Xu and Yahya Rahmat-Samii}, journal={IEEE Transactions on Antennas and Propagation}, volume= 55, issue= 3, date={}, part1={ March 2007 Page(s):760 - 765 }, abstract={In order to enforce particles to search inside the solution space of interest during the optimization procedure, various boundary conditions are currently used in particle swarm optimization (PSO) algorithms. The performances, however, vary considera..... } } @article{ieeebibJ118, title={ New Chaotic PSO-Based Neural Network Predictive Control for Nonlinear Process}, author={Ying Song and Zengqiang Chen and Zhuzhi Yuan}, journal={IEEE Transactions on Neural Networks}, volume= 18, issue= 2, date={ March 2007}, pages={595 - 601 }, year={2007}, abstract={In this letter, a novel nonlinear neural network (NN) predictive control strategy based on the new tent-map chaotic particle swarm optimization (TCPSO) is presented. The TCPSO incorporating tent-map chaos, which can avoid trapping to local minima and..... } } @article{ieeebibJ119, title={ A Multiobjective Memetic Algorithm Based on Particle Swarm Optimization}, author={Dasheng Liu and K. C. Tan and C. K. Goh and W. K. Ho}, journal={IEEE Transactions on Systems, Man and Cybernetics, Part B}, volume= 37, issue= 1, date={ Feb. 2007}, pages={42 - 50 }, year={2007}, abstract={In this paper, a new memetic algorithm (MA) for multiobjective (MO) optimization is proposed, which combines the global search ability of particle swarm optimization with a synchronous local search heuristic for directed local fine-tuning. A new part..... } } @inproceedings{ieeebib12, title={ A discrete particle swarm optimizer for graphic presentation of GMDH network}, author = {Te-Chen Liu and Ji-Chang Wang}, booktitle={2005 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 3, 10-12 Oct. 2005}, year={2005}, pages={2329 - 2333 Vol. 3}, abstract={Particle swarm optimization is a new population based optimization methodology. With a characteristic of high performance and easy implementation, the particle swarm optimizer has many successful cases. However, it still has a problem of efficiency i..... } } @article{ieeebibJ120, title={ An RBF Network With OLS and EPSO Algorithms for Real-Time Power Dispatch}, author={C.-M. Huang and F.-L. Wang}, journal={IEEE Transactions on Power Systems}, volume= 22, issue= 1, date={ Feb. 2007}, pages={96 - 104 }, year={2007}, abstract={This paper proposes a novel technique that combines orthogonal least-squares (OLS) and enhanced particle swarm optimization (EPSO) algorithms to construct the radial basis function (RBF) network for real-time power dispatch (RTPD). The goals consider..... } } @article{ieeebibJ121, title={ Comparison of Nonuniform Optimal Quantizer Designs for Speech Coding With Adaptive Critics and Particle Swarm}, author={G. K. Venayagamoorthy and W. Zha}, journal={IEEE Transactions on Industry Applications}, volume= 43, issue= 1, date={ Jan.-feb. 2007}, pages={238 - 244 }, year={2007}, abstract={This paper presents the design of a companding nonuniform optimal scalar quantizer for speech coding. The quantizer is designed using two neural networks to perform the nonlinear transformation. These neural networks are used in the front and back en..... } } @article{ieeebibJ122, title={ A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems}, author={A. I. Selvakumar and K. Thanushkodi}, journal={IEEE Transactions on Power Systems}, volume= 22, issue= 1, date={ Feb. 2007}, pages={42 - 51 }, year={2007}, abstract={This paper proposes a new version of the classical particle swarm optimization (PSO), namely, new PSO (NPSO), to solve nonconvex economic dispatch problems. In the classical PSO, the movement of a particle is governed by three behaviors, namely, iner..... } } @inproceedings{ieeebib123, title={ Some Insight Over New Variations of the Particle Swarm Optimization Method}, author = {S. Selleri and M. Mussetta and P. Pirinoli and R.E. Zich and L. Matekovits}, booktitle={Antennas and Wireless Propagation Letters}, notes={Volume 5, Issue 1, Dec. 2006}, year={2006}, pages={235 - 238 }, abstract={The Particle Swarm Optimization (PSO) method recently gained high popularity in electromagnetics. Here few variations over the standard algorithm, referred to as Meta PSO, are proposed and the results of their application to the optimization of a mic..... } } @inproceedings{ieeebib124, title={ The Design of Miniature Three-Element Stochastic Yagi-Uda Arrays Using Particle Swarm Optimization}, author = {Z. Bayraktar and P.L. Werner and D.H. Werner}, booktitle={Antennas and Wireless Propagation Letters}, notes={Volume 5, Issue 1, Dec. 2006}, year={2006}, pages={22 - 26 }, abstract={A fixed grid structure of reduced length is employed to generate three-element miniature stochastic Yagi-Uda arrays. Particle swarm optimization (PSO) is utilized to alter the shape and the element distances for optimum forward gain, good front-to-ba..... } } @article{ieeebibJ125, title={ A Comparative Study on Particle Swarm Optimization for Optimal Steady-State Performance of Power Systems}, author={J.G. Vlachogiannis and K.Y. Lee}, journal={IEEE Transactions on Power Systems}, volume= 21, issue= 4, date={ Nov. 2006}, pages={1718 - 1728 }, year={2006}, abstract={In this paper, three new particle swarm optimization (PSO) algorithms are compared with the state of the art PSO algorithms for the optimal steady-state performance of power systems, namely, the reactive power and voltage control. Two of the three in..... } } @article{ieeebibJ126, title={ The Formulation of the Optimal Strategies for the Electricity Producers Based on the Particle Swarm Optimization Algorithm}, author={Y. Ma and C. Jiang and Z. Hou and C. Wang}, journal={IEEE Transactions on Power Systems}, volume= 21, issue= 4, date={ Nov. 2006}, pages={1663 - 1671 }, year={2006}, abstract={In competitive electricity markets, the producer as a market participant strives to find the optimal supply function with the objective of maximizing his/her producer surplus in the market clearing. The model of the producer surplus maximization is a..... } } @article{ieeebibJ127, title={ Using the Particle Swarm Evolutionary Approach in Shape Optimization and Field Analysis of Devices Involving Nonlinear Magnetic Media}, author={A.A. Adly and S.K. Abd-El-Hafiz}, journal={IEEE Transactions on Magnetics}, volume= 42, issue= 10, date={ Oct. 2006}, pages={3150 - 3152 }, year={2006}, abstract={Extensive efforts have been long directed towards the development of shape optimization methodologies for electromagnetic devices. In case of devices involving nonlinear magnetic media, this optimization process becomes more complicated. This paper d..... } } @article{ieeebibJ128, title={ An integrated multiscaling strategy based on a particle swarm algorithm for inverse scattering problems}, author={M. Donelli and G. Franceschini and A. Martini and A. Massa}, journal={IEEE Transactions on Geoscience and Remote Sensing}, volume= 44, issue= 2, date={ Feb. 2006}, pages={298 - 312 }, year={2006}, abstract={The application of a multiscale strategy integrated with a stochastic technique to the solution of nonlinear inverse scattering problems is presented. The approach allows the explicit and effective handling of many difficulties associated with such p..... } } @article{ieeebibJ129, title={ A particle swarm optimization method with enhanced global search ability for design optimizations of electromagnetic devices}, author={S.L. Ho and Shiyou Yang and Guangzheng Ni and H.C. Wong}, journal={IEEE Transactions on Magnetics}, volume= 42, issue= 4, date={ April 2006}, pages={1107 - 1110 }, year={2006}, abstract={Based on the refinement successes to particle swarm optimization (PSO) methods, which include, namely, the introduction of an age variable, the proposal of new selection strategies to find the best solutions of the particle as well as for its neighbo..... } } @inproceedings{ieeebib13, title={ Principal component particle swarm optimization (PCPSO)}, author = {M.S. Voss}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={401 - 404}, abstract={Particle swarm optimization (PSO) is based on the notion of particles flying through solution space. Each particle is assumed to have n-dimensions that are mapped to the variables of the function that is being evaluated. The standard PSO algorithm up..... } } @article{ieeebibJ130, title={ Multiobjective control of power plants using particle swarm optimization techniques}, author={J.S. Heo and K.Y. Lee and R. Garduno-Ramirez}, journal={IEEE Transactions on Energy Conversion}, volume= 21, issue= 2, date={ June 2006}, pages={552 - 561 }, year={2006}, abstract={Multiobjective optimal power plant operation requires an optimal mapping between unit load demand and pressure set point in a fossil fuel power unit (FFPU). In general, the optimization problem with varying unit load demand cannot be solved using a f..... } } @article{ieeebibJ131, title={ A particle-swarm-optimized fuzzy-neural network for voice-controlled robot systems}, author={A. Chatterjee and K. Pulasinghe and K. Watanabe and K. Izumi}, journal={IEEE Transactions on Industrial Electronics}, volume= 52, issue= 6, date={ Dec. 2005}, pages={1478 - 1489 }, year={2005}, abstract={This paper shows the possible development of particle swarm optimization (PSO)-based fuzzy-neural networks (FNNs) that can be employed as an important building block in real robot systems, controlled by voice-based commands. The PSO is employed to tr..... } } @article{ieeebibJ132, title={ Particle swarm optimization approaches to coevolve strategies for the iterated prisoner's dilemma}, author={N. Franken and A.P. Engelbrecht}, journal={IEEE Transactions on Evolutionary Computation}, volume= 9, issue= 6, date={ Dec. 2005}, pages={562 - 579 }, year={2005}, abstract={This paper presents and investigates the application of coevolutionary training techniques based on particle swarm optimization (PSO) to evolve playing strategies for the nonzero sum problem of the iterated prisoner's dilemma (IPD). Three different c..... } } @article{ieeebibJ133, title={ Application of a parallel particle swarm optimization scheme to the design of electromagnetic absorbers}, author={S. Cui and D.S. Weile}, journal={IEEE Transactions on Antennas and Propagation}, volume= 53, issue= 11, date={ Nov. 2005}, pages={3616 - 3624 }, year={2005}, abstract={The application of parallel (synchronous) particle swarm optimization (PSO) to electromagnetic absorber design is described. Synchronous PSO is a version of PSO that allows for parallelization and hence faster optimization. The velocity updating rule..... } } @article{ieeebibJ134, title={ Parallel particle swarm optimization and finite- difference time-domain (PSO/FDTD) algorithm for multiband and wide-band patch antenna designs}, author={N. Jin and Y. Rahmat-Samii}, journal={IEEE Transactions on Antennas and Propagation}, volume= 53, issue= 11, date={ Nov. 2005}, pages={3459 - 3468 }, year={2005}, abstract={This paper presents a novel evolutionary optimization methodology for multiband and wide-band patch antenna designs. The particle swarm optimization (PSO) and the finite-difference time-domain (FDTD) are combined to achieve the optimum antenna satisf..... } } @article{ieeebibJ135, title={ Handling multiple objectives with particle swarm optimization}, author={C.A.C. Coello and G.T. Pulido and M.S. Lechuga}, journal={IEEE Transactions on Evolutionary Computation}, volume= 8, issue= 3, date={ June 2004}, pages={256 - 279 }, year={2004}, abstract={This paper presents an approach in which Pareto dominance is incorporated into particle swarm optimization (PSO) in order to allow this heuristic to handle problems with several objective functions. Unlike other current proposals to extend PSO to sol..... } } @inproceedings{ieeebib136, title={ Particle Swarm Optimization for Economic Power Dispatch with Valve-Point Effects}, author = {C. H. Chen and S. N. Yeh}, booktitle={Transmission \& Distribution Conference and Exposition: Latin America, 2006. TDC '06. IEEE/PES}, notes={Aug. 2006}, year={2006}, pages={1 - 5 }, abstract={In this paper, four modified versions of particle swarm optimizer (PSO) have been applied to the economic power dispatch with valve-point effects. In order to obtain the optimal solution, traditional PSO search a new position around the current posit..... } } @inproceedings{ieeebib137, title={ Study on Secondary Voltage Control Based on Multi-agent Particle Swarm Optimization Algorithm}, author = {Z.W. Jia and J. Liu and X.M. Xie}, booktitle={International Conference on Power System Technology, 2006. PowerCon 2006. }, notes={Oct. 2006}, year={2006}, pages={1 - 5 }, abstract={Secondary voltage control system is a significant segment of the hierarchical voltage control in power systems. Though voltage controller has both constant voltage regulators, such as generators and static reactive power compensators, and discrete vo..... } } @inproceedings{ieeebib138, title={ Study of Probabilistic Available Transfer Capability by Improved Particle Swarm Optimization}, author = {Ruiyang Zhang and Guoqing Li and Houhe Chen}, booktitle={International Conference on Power System Technology, 2006. PowerCon 2006. }, notes={Oct. 2006}, year={2006}, pages={1 - 6 }, abstract={This paper presents a new model of probabilistic Available Transfer Capability (abr. ATC) computation, which is based on the improved particle swarm optimization (abr. IPSO). Firstly, pointing to the search characteristics of particle swarm optimizat..... } } @inproceedings{ieeebib139, title={ An Improved Particle Swarm Optimization and Its Application to Power System Transfer Capability Calculation}, author = {Chang-hua Zhang and Rong-fu Sun and Chong-xu Liu and Yue Fan and Shuan-bao Niu and Yong-hua Song}, booktitle={International Conference on Power System Technology, 2006. PowerCon 2006. }, notes={Oct. 2006}, year={2006}, pages={1 - 5 }, abstract={In this paper, an algorithm based on Particle Swarm Optimization (PSO) for power system transfer capability calculation is presented. A dual fitness scheme that takes both objective and constraint into account is adopted to evaluate the survival chan..... } } @inproceedings{ieeebib14, title={ A hybrid particle swarm algorithm with embedded chaotic search}, author = {Hong-Ji Meng and Peng Zheng and Rong-Yang Wu and Xiao-Jing Hao and Zhi Xie}, booktitle={2004 IEEE Conference on Cybernetics and Intelligent Systems}, note={Volume 1, 1-3 Dec. 2004}, year={2004}, pages={367 - 371 vol.1 }, abstract={A new hybrid evolutionary-based method combining the particle swarm algorithm and the chaotic search is proposed for optimizing. To achieve high performance in optimizing, the chaotic search mechanism is embedded in the standard particle swarm algori..... } } @inproceedings{ieeebib140, title={ Improvement of Particle Swarm Optimization for High-Dimensional Space}, author = {T. Korenaga and T. Hatanaka and K. Uosaki}, booktitle={SICE-ICASE, 2006. International Joint Conference}, notes={Oct. 2006}, year={2006}, pages={2174 - 2178 }, abstract={Particle Swarm Optimization (PSO) is a population-based search methodology inspired by social behavior observed in nature, such as flocks of birds and schools of fish. In many studies, PSO has been successful in a variety of optimization problems. Th..... } } @inproceedings{ieeebib141, title={ Particle Swarm Optimization and Finite-Element Based Approach for Induction Heating Cooker Design}, author = {S.H. Hosseini and A.M. Kashtiban and G. Alizadeh}, booktitle={SICE-ICASE, 2006. International Joint Conference}, notes={Oct. 2006}, year={2006}, pages={4624 - 4627 }, abstract={In this paper a novel approach for induction heating (IH) design is presented. The powerful particle swarm optimization (PSO) and finite-element method (FEM) are combined together to allow optimal induction heating design. For this purpose cost funct..... } } @inproceedings{ieeebib142, title={ Increment PID Controller Based on Immunity Particle Swarm Optimization Algorithm}, author = {Wei Zhng and Kun Wang and Shouzhi-Li}, booktitle={IMACS Multiconference on Computational Engineering in Systems Applications}, notes={Oct. 2006}, year={2006}, pages={1947 - 1951 }, abstract={Based on the astringency and practicability of Particle Swarm Optimization Algorithm(PSO) and T cell's promotions and B cell's restrainability of Immunity Particle Swarm Optimization Algorithm(IMPSO) and applied it to PID controllers. It is clear tha..... } } @inproceedings{ieeebib143, title={ Particle Swarm Optimized Polynomials for Data Classification}, author = {B.B. Misra and S.C. Satapathy and P.K. Dash}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06. }, notes={Volume 1, Oct. 2006}, year={2006}, pages={649 - 654 }, abstract={Data classification is an important area of data mining. Several well known techniques such as decision tree, neural network, etc. are available for this task. In this paper we propose a particle swarm optimized polynomial equation for classification..... } } @inproceedings{ieeebib144, title={ The Design of Neural Network Direct Inverse Controller Based on Complex Particle Swarm Optimization Algorithm}, author = {Yuan-bin Mo and He-tong Liu}, booktitle={Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2006. SYNASC '06. }, notes={Sept. 2006}, year={2006}, pages={382 - 388 }, abstract={Aiming at the difficulties of knowledge acquisition of training data in the neural network direct inverse control, method for generalizing design method of neuro-controllers was proposed. After analyzing the Method of Complex (MC) and Particle Swarm ..... } } @inproceedings{ieeebib145, title={ Economic Dispatch of Power Systems Based on the Modified Particle Swarm Optimization Algorithm}, author = {Yun-He Hou and Li-Juan Lu and Xin-Yin Xiong and Yao-Wu Wu}, booktitle={Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES}, notes={2005}, year={2005}, pages={1 - 6 }, abstract={This paper presents a new versatile optimization algorithm called modified particle swarm optimization algorithm (MPSO) for solving the economic dispatch (ED) problem of power systems. Compared with the classical PSO algorithm, several modified opera..... } } @inproceedings{ieeebib146, title={ Environmental/Economic Transaction Planning Using Multiobjective Particle Swarm Optimization and Non-Stationary Multi-Stage Assignment Penalty Function}, author = {Rui Ma and Peng Wang and Huachun Yang and Guoqiang Hu}, booktitle={Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES}, notes={2005}, year={2005}, pages={1 - 6 }, abstract={This paper presents a new approach for environmental/economic transaction planning model of the electricity market. The environmental/economic transaction planning problem is formulated as a multi-objective optimal power flow (MOPF) problem. A novel ..... } } @inproceedings{ieeebib147, title={ Local Optimum Embranchment Based Convergence Guarantee Particle Swarm Optimization and Its Application in Transmission Network Planning}, author = {Yi-Xiong Jin and Hao-Zhong Cheng and Jian-Yong Yan and Li Zhang}, booktitle={Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES}, notes={2005}, year={2005}, pages={1 - 6 }, abstract={This paper summarizes some improved methods of particle swarm optimization (PSO), analyses its critical reasons in convergence dilemma, and then puts forward local optimum embranchment optimization method and local depth optimization method according..... } } @inproceedings{ieeebib148, title={ An Improved Particle Swarm Optimization Algorithm for Multistage and Coordinated Planning of Transmission Systems}, author = {Chen Yuehui and Chen Haiyan and Chen Jinfu and Duan Xianzhong}, booktitle={Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES}, notes={2005}, year={2005}, pages={1 - 6 }, abstract={This paper presents a new model of multistage and coordinated planning of transmission systems. Reliability constraints are considered in this model. Particle swarm algorithm is improved and applied to the multistage planning, which is available to h..... } } @inproceedings{ieeebib149, title={ Relative Velocity Updating in Parallel Particle Swarm Optimization Based Lagrangian Relaxation for Large-scale Unit Commitment Problem}, author = {S. Chusanapiputt and D. Nualhong and S. Jantarang and S. Phoomvuthisarn}, booktitle={TENCON 2005 2005 IEEE Region 10}, notes={Nov. 2005}, year={2005}, pages={1 - 6 }, abstract={This paper presents an effectiveness of combined Parallel Relative Particle Swarm Optimization (PRPSO) and Lagrangian Relaxation (LR) for a large-scale constrained Unit Commitment (UC) problem in electric power system. The proposed algorithm incorpor..... } } @inproceedings{ieeebib15, title={ Nonlinear particle swarm optimizer: framework and the implementation of optimization}, author = {Cui Zhihua and Zeng Jianchao}, booktitle={Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th}, notes={Volume 1, 6-9 Dec. 2004}, year={2004}, pages={238 - 241 Vol. 1 }, abstract={Particle swarm optimizer (PSO) is a new evolutionary computation method, which has been successfully applied to many fields. Through mechanism analysis of the standard particle swarm optimizer, a linear equivalent representation of the velocity updat..... } } @inproceedings{ieeebib150, title={ A New Strategy of Acceleration Coefficients for Particle Swarm Optimization}, author = {Wenzhong Guo and Guolong Chen and Xiang Feng}, booktitle={10th International Conference on Computer Supported Cooperative Work in Design}, notes={May 2006}, year={2006}, pages={1 - 5 }, abstract={Acceleration coefficients controlled the impact of the particle's own experiences and the other particles' experiences on the trajectory of each particle. The setting of acceleration played a key role in the performance of particle swarm optimization..... } } @inproceedings{ieeebib151, title={ Personal Best Oriented Constriction Type Particle Swarm Optimization}, author = {Chang-Huang Chen and Sheng-Nian Yeh}, booktitle={2006 IEEE Conference on Cybernetics and Intelligent Systems}, abstract={To solve the problem of network expansion, an improved particle swarm optimization algorithm (PSO) is proposed in this paper. This method initialized the particle swarm according to borderline search mind, made the initialized particle near the safet..... } } @inproceedings{ieeebib152, title={ An Improved Particle Swarm Optimization Method Based on Borderline Search Strategy for Transmission Network Expansion Planning}, author={Dong-Xiao Niu and Yun-Peng Ling and Qi Zhao and Qing-Ying Zhao}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={2846 - 2850}, abstract={To solve the problem of network expansion, an improved particle swarm optimization algorithm (PSO) is proposed in this paper. This method initialized the particle swarm according to borderline search mind, made the initialized particle near the safet..... } } @inproceedings{ieeebib153, title={ A Hybrid Particle Swarm Optimization Algorithm for Predicting the Chaotic Time Series}, author = {Wei Liu and Kejun Wang and Bing Sun and Keyong Shao}, booktitle={Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation}, notes={June 2006}, year={2006}, pages={2454 - 2458}, abstract={A novel hybrid particle swarm optimization(HPSO) is proposed, which the gradint descent learning algorithm is combined with modified particle swarm optimization (MPSO).Firstly, The MPSO was determined by linearly decreasing inertia weight and constri..... } } @inproceedings{ieeebib154, title={ A New CLARANS Algorithm Based on Particle Swarm Optimization}, author = {Xiyu Liu and Hong Liu}, booktitle={2006. CIT '06. The Sixth IEEE International Conference on Computer and Information Technology}, notes={Sept. 2006}, year={2006}, pages={12 - 12}, abstract={CLARANS is an efficient and effective clustering method especially in spatial data mining. It is applicable to locate objects with polygon shape. Inspired by its randomized searching nature, and based on the standard particle swarm optimization PSO ..... } } @inproceedings{ieeebib155, title={ Reconfiguration of network skeleton based on discrete particle-swarm optimization for black-start restoration}, author = {Yan Liu and Xueping Gu}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={7 pp. }, abstract={The black start restoration of a power system after a complete blackout is a very important issue to safety of the power system. The reasonable network reconfiguration strategy is necessary for establishing the main network and restoring loads as soo..... } } @inproceedings{ieeebib156, title={ Coordinated aggregation particle swarm optimization applied in reactive power and voltage control}, author = {J.G. Vlachogiannis and K.Y. Lee}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={6 pp. }, abstract={This paper introduces a new particle swarm optimization (PSO) algorithm called coordinated aggregation (CA) PSO, which simulates how the achievements of particles are distributed in the entire swarm affecting its manipulation. Specifically, at each i..... } } @inproceedings{ieeebib157, title={ Stochastic combined heat and power dispatch based on multi-objective particle swarm optimization}, author = {Lingfeng Wang and Chanan Singh}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={8 pp. }, abstract={Conventional economic power dispatch problem uses deterministic models, which are however not able to reflect some real situations in practical applications. Since certain inaccurate and uncertain factors are normally involved in system operations, s..... } } @inproceedings{ieeebib158, title={ Particle swarm localization of acoustic sources in the presence of reverberation}, author = {R. Parisi and P. Croene and A. Uncini}, booktitle={Proceedings of the IEEE International Symposium on Circuits and Systems, 2006. ISCAS 2006. }, notes={21-24 May 2006}, year={2006}, pages={4 pp. }, abstract={In this work a novel approach to acoustic source localization in reverberant environments is introduced. The proposed method effectively employs particle filtering (PF) and particle swarm optimization (PSO) in an integrated framework. Source localiza..... } } @inproceedings{ieeebib159, title={ A particle swarm optimization-based approach for pricing VAR providers in the electricity market with the consideration of voltage security}, author = {E.E. El-Araby and N. Yorino}, booktitle={2005 International Conference on Future Power Systems}, notes={16-18 Nov. 2005}, year={2005}, pages={6 pp. }, abstract={This paper introduces an integration of particle swarm optimization "PSO" and successive linear programming "SLP" for dealing with VAR ancillary service problem in a competitive market-based environment. The main target of the developed market is to ..... } } @inproceedings{ieeebib16, title={ Hybrid particle swarm optimization with simulated annealing}, author = {Xi-Huai Wang and Jun-Jun Li}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004. }, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2402 - 2405 vol.4 }, abstract={Particle swarm optimization is a recently invented intelligent optimizer with several highly desirable attributes. A hybrid particle swarm optimization is proposed. This method integrates the particle swarm optimization with simulated annealing. The ..... } } @inproceedings{ieeebib160, title={ Voltage flicker measurement using particle swarm optimization technique for power quality assessment}, author = {A.K. Al-Othman and K.M. El-Nagger}, booktitle={Electrotechnical Conference, 2006. MELECON 2006. IEEE Mediterranean}, notes={16-19 May 2006}, year={2006}, pages={1077 - 1082 }, abstract={Measurements of voltage flicker levels and its frequency is of great concern to the utility in order to prevent unacceptable voltage fluctuation in the supplying system and to evaluate the power quality. This paper introduces a new digital approach f..... } } @inproceedings{ieeebib161, title={ A unified scheme for testing alternative techniques for distribution system minimum loss reconfiguration}, author = {F. Batrinu and E. Carpaneto and G. Chicco}, booktitle={2005 International Conference on Future Power Systems}, notes={16-18 Nov. 2005}, year={2005}, pages={6 pp. }, abstract={The optimal reconfiguration of a large distribution system is a global optimisation problem typically solved by using deterministic or heuristic methods. Comparing the effectiveness of the various methods can be assisted by formulating a unified fram..... } } @inproceedings{ieeebib162, title={ A novel path planning for mobile robots using modified particle swarm optimizer}, author = {Kaiyou Lei and Yuhui Qiu and Yi He}, booktitle={1st International Symposium on Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006}, notes={19-21 Jan. 2006}, year={2006}, pages={4 pp. }, abstract={Path planning for mobile robots is an important topic in modern robotics. This paper proposes a novel approach to path planning problem for mobile robots, in which the model of the vertexes of obstacles is constructed to describe two-dimensional map ..... } } @inproceedings{ieeebib163, title={ Automatic landing control using particle swarm optimization}, author = {Jih-Gau Juang and Bo-Shian Lin and Kuo-Chih Chin}, booktitle={2005. ICM '05. IEEE International Conference on Mechatronics}, notes={10-12 July 2005}, year={2005}, pages={721 - 726}, abstract={This paper proposes an intelligent aircraft automatic landing controller that uses fuzzy-neural controller with particle swarm optimization to improve the performance of conventional automatic landing system. Control gains are selected by a parameter..... } } @inproceedings{ieeebib164, title={ A fast hybrid algorithm for global optimization}, author = {Yong-Jun Wang and Jiang-She Zhang and Yu-Fen Zhang}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 5, 18-21 Aug. 2005}, year={2005}, pages={3030 - 3035 Vol. 5 }, abstract={An algorithm, consisting of gradient descent technique and particle swarm optimization (PSO) method for global optimization is proposed. The gradient descent technique is used to find a local minimum of objective function fast and efficiently, and pa..... } } @inproceedings{ieeebib165, title={ A modified particle swarm optimization algorithm}, author = {Qian-Li Zhang and Xing Li and Quang-Ahn Tran}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 5, 18-21 Aug. 2005}, year={2005}, pages={2993 - 2995 Vol. 5 }, abstract={A modified particle swarm optimization (PSO) algorithm is proposed in this paper to avoid premature convergence with the introduction of mutation operation. The performance of this algorithm is compared to the standard PSO algorithm and experiments i..... } } @inproceedings{ieeebib166, title={ Adaptive particle swarm optimizer for beam angle selection in radiotherapy planning}, author = {Yongjie Li and Dezhong Yao and Wufan Chen}, booktitle={2005 IEEE International Conference Mechatronics and Automation}, notes={Volume 1, 29 July-1 Aug. 2005}, year={2005}, pages={421 - 425 Vol. 1}, abstract={As an emerging stochastic optimization paradigm, particle swarm optimization (PSO) algorithm has received a lot of attention in recent years. In this paper, a method named adaptive PSO is introduced to automatically select the beam angles for intensi..... } } @inproceedings{ieeebib167, title={ Robust adaptive particle swarm optimization}, author = {G. Ueno and K. Yasuda and N. Iwasaki}, booktitle={2005 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 4, 10-12 Oct. 2005}, year={2005}, pages={3915 - 3920 Vol. 4}, abstract={It is well known that particle swarm optimization (PSO), which was originally proposed by J. Kennedy et al., is a powerful algorithm for solving unconstrained and constrained global optimization problems. Appropriate adjustment of its parameters, how..... } } @inproceedings{ieeebib168, title={ Improved particle swarm optimization algorithm for optimum steelmaking charge plan based on the pseudo TSP solution}, author = {Yun-Can Xue and Qi-Wen Yang and Jun Feng}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 9, 18-21 Aug. 2005}, year={2005}, pages={5452 - 5457 Vol. 9 }, abstract={An optimum furnace charge plan model for steelmaking continuous casting planning and scheduling is presented. A pseudo travel salesman problem model is presented to describe the model. An improved particle swarm optimization is presented to solve the..... } } @inproceedings{ieeebib169, title={ Fuzzy rule extraction by two-objective particle swarm optimization and application for taste identification of tea}, author = {Ming Ma and Chun-Guang Zhou and Li-Biao Zhang and Quan-Sheng Dou}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 9, 18-21 Aug. 2005}, year={2005}, pages={5690 - 5694 Vol. 9 }, abstract={The extraction of fuzzy rules is always a difficult problem to fuzzy system, in this problem performance and complexity are two conflicting criteria. We have proposed a two-objective algorithm based on particle swarm optimization algorithm and the we..... } } @inproceedings{ieeebib17, title={ Particle swarm optimization algorithm for single machine total weighted tardiness problem}, author = {M.F. Tasgetiren and M. Sevkli and Yun-Chia Liang and G. Gencyilmaz}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 2, 19-23 June 2004}, year={2004}, pages={1412 - 1419 Vol.2 }, abstract={In This work we present a particle swarm optimization algorithm to solve the single machine total weighted tardiness problem. A heuristic rule, the smallest position value (SPV) rule, is developed to enable the continuous particle swarm optimization ..... } } @inproceedings{ieeebib170, title={ Improving cascading classifiers with particle swarm optimization}, author = {L.S. Oliveira and A.S., Jr. Britto and R. Sabourin}, booktitle={Eighth International Conference on Document Analysis and Recognition, 2005. Proceedings}, notes={29 Aug.-1 Sept. 2005}, year={2005}, pages={570 - 574 Vol. 2 }, abstract={This paper addresses the issue of class related reject thresholds for cascading classifier systems. It has been demonstrated in the literature that class related reject thresholds provide an error-reject tradeoff better than a single global threshold..... } } @inproceedings{ieeebib171, title={ Particle swarm optimization of fuzzy logic controller for high quality RRM auto-tuning of UMTS networks}, author = {H. Dubreil and Z. Altman and V. Diascorn and J.-M. Picard and M. Clerc}, booktitle={Vehicular Technology Conference, 2005. VTC 2005-Spring. 2005 IEEE 61st}, notes={Volume 3, 30 May-1 June 2005}, year={2005}, pages={1865 - 1869 Vol. 3 }, abstract={Auto-tuning of radio resource management (RRM) parameters using fuzzy logic controllers (FLCs) has recently been introduced as a means to enhance UMTS network performance and adapt it to traffic variations. This paper presents a methodology for optim..... } } @inproceedings{ieeebib172, title={ A comparison of particle swarms techniques for the development of quantitative structure-activity relationship models for drug design}, author = {W. Cedeno and D. Agrafiotis}, booktitle={Computational Systems Bioinformatics Conference, 2005. Workshops and Poster Abstracts. IEEE}, notes={8-11 Aug. 2005}, year={2005}, pages={322 - 331 }, abstract={The development of quantitative structure-activity relationship (QSAR) models for computer-assisted drug design is a well-known technique in the pharmaceutical industry. QSAR models provide medicinal chemists with mechanisms for predicting the biolog..... } } @inproceedings{ieeebib173, title={ Particle swarm approach for retiming in VLSI}, author = {A. Paul and T.A.A. Victoire and A.E. Jeyakumar}, booktitle={Proceedings of the 46th IEEE International Midwest Symposium on Circuits and Systems, 2003. MWSCAS '03}, notes={Volume 3, 27-30 Dec. 2003}, year={2003}, pages={1532 - 1535 Vol. 3 }, abstract={Retiming is a design technique used to reposition the memory elements of a circuit while preserving its functionality. This paper suggests a novel approach by which solution to the retiming problem can be achieved; Particle Swarm approach is the one ..... } } @inproceedings{ieeebib174, title={ Hybrid particle swarm with differential evolution for multimodal image registration}, author = {H. Talbi and M. Batouche}, booktitle={2004. IEEE ICIT '04. 2004 IEEE International Conference on Industrial Technology}, notes={Volume 3, 8-10 Dec. 2004}, year={2004}, pages={1567 - 1572 Vol. 3}, abstract={In this paper, we propose an algorithm of hybrid particle swarm with differential evolution (DE) operator, termed DEPSO, to solve the problem of multimodal image registration. This algorithm combines the robustness of entropy based measures and the s..... } } @inproceedings{ieeebib175, title={ Combined algorithm for time-varying system based on improved particle swarm optimization and EWRLS algorithm}, author = {Wei Jian and Yuncan Xue and Jiao Huang}, booktitle={2004. IEEE ICIT '04. 2004 IEEE International Conference on Industrial Technology}, notes={Volume 3, 8-10 Dec. 2004}, year={2004}, pages={1474 - 1477 Vol. 3}, abstract={A combined algorithm based on the improved particle swarm optimization (PSO) and EWRLS algorithm is presented in this paper. A modified particle swarm optimization with velocity is also presented to enhance the response speed of PSO algorithm. The se..... } } @inproceedings{ieeebib176, title={ Improved particle swarm optimization algorithms study based on the neighborhoods topologies}, author = {Wei Jian and Yuncan Xue and Jixin Qian}, booktitle={Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE}, notes={Volume 3, 2-6 Nov. 2004}, year={2004}, pages={2192 - 2196 Vol. 3 }, abstract={A study of neighborhoods topologies on particle swarm optimization for complex functions is discussed. The suitability of three topologies to the kind of functions is experimented. The convergence features affected by neighborhoods topologies on comp..... } } @inproceedings{ieeebib177, title={ Nonparametric density estimation based independent component analysis via particle swarm optimization}, author = {D.J. Krusienski and W.K. Jenkins}, booktitle={Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '05).}, notes={Volume 4, 18-23 March 2005}, year={2005}, pages={iv/357 - iv/360 Vol. 4}, abstract={The paper investigates the application of a modified particle swarm optimization technique to nonparametric density estimation based independent component analysis (ICA). Nonparametric ICA has the advantage over traditional ICA techniques in that its..... } } @inproceedings{ieeebib178, title={ Particle swarm optimization of a modified Bernstein polynomial for conformal array excitation synthesis}, author = {D.W. Boeringer and D.H. Werner}, booktitle={Antennas and Propagation Society International Symposium, 2004. IEEE}, notes={Volume 3, 20-25 June 2004}, year={2004}, pages={2293 - 2296 Vol.3 }, abstract={Bernstein polynomials are well known in the computer graphics community as the basis functions of Bezier curves. Like popular amplitude weighting functions, such as Taylor weights, Bernstein polynomials are nonnegative and decay smoothly from a singl..... } } @inproceedings{ieeebib179, title={ Gaussian swarm: a novel particle swarm optimization algorithm}, author = {R.A. Krohling}, booktitle={2004 IEEE Conference on Cybernetics and Intelligent Systems}, note={Volume 1, 1-3 Dec. 2004}, year={2004}, pages={372 - 376 vol.1 }, abstract={In this paper, a novel particle swarm optimization algorithm based on the Gaussian probability distribution is proposed. The standard particle swarm optimization (PSO) algorithm has some parameters that need to be specified before using the algorithm..... } } @inproceedings{ieeebib18, title={ A comparison of particle swarm optimization and genetic algorithms for a phased array synthesis problem}, author = {D.W. Boeringer and D.H. Werner}, booktitle={Antennas and Propagation Society International Symposium, 2003. IEEE}, notes={Volume 1, 22-27 June 2003}, year={2003}, pages={181 - 184 vol.1 }, abstract={Particle swarm optimization is a recently invented high-performance optimizer that possesses several highly desirable attributes, including the fact that the basic algorithm is very easy to understand and implement. It is similar in some ways to gene..... } } @inproceedings{ieeebib180, title={ Grouped-and-delayed broadcasting mechanism for optimum information in particle swarm optimization}, author = {Lei Wang and Qi Kang and Qidi Wu}, booktitle={2004 IEEE Conference on Cybernetics and Intelligent Systems}, note={Volume 1, 1-3 Dec. 2004}, year={2004}, pages={372 - 376 vol.1 }, abstract={In this paper, the grouped-and-delayed mechanism for optimum information broadcasting is introduced into optimization process of particle swarm optimization algorithm to make sufficient search in optimization space and to meet the requirement of gene..... } } @inproceedings{ieeebib181, title={ Hybrid particle swarm optimizer with line search}, author = {Yu Liu and Zheng Qin and Zhewen Shi}, booktitle={2004 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 4, 10-13 Oct. 2004}, year={2004}, pages={3751 - 3755 vol.4}, abstract={Particle swarm optimization, a new good swarm intelligence paradigm, has been successfully applied to many non-linear optimization problems. In a swarm each particle adjusts it's flying toward a promising area depending on cooperative interaction wit..... } } @inproceedings{ieeebib182, title={ Particle swarm optimization for base station placement in mobile communication}, author = {Zhang Yangyang and Ji Chunlin and Yuan Ping and Li Manlin and Wang Chaojin and Wang Guangxing}, booktitle={2004 IEEE International Conference on Networking, Sensing and Control}, notes={Volume 1, 21-23 March 2004}, year={2004}, pages={428 - 432 Vol.1}, abstract={The tremendous growth in the demand for mobile services results in an explosion in base station (BS) density and network complexity, making the conventional manual planning processes highly inefficient. In this paper, we give some novel adaptation to..... } } @inproceedings{ieeebib183, title={ Particle swarm optimization for mobile ad hoc networks clustering}, author = {Chunlin Ji and Yangyang Zhang and Shixing Gao and Ping Yuan and Zhe Li}, booktitle={2004 IEEE International Conference on Networking, Sensing and Control}, notes={Volume 1, 21-23 March 2004}, year={2004}, pages={372 - 375 Vol.1}, abstract={A mobile ad hoc network is an infrastructureless wireless network that can support highly dynamic mobile nodes. The multi-hop feature of an ad hoc network suggests the use of clustering to simplify routing and management. In this work, we propose a r..... } } @inproceedings{ieeebib184, title={ Adaptive critics for dynamic particle swarm optimization}, author = {G.K. Venayagamoorthy}, booktitle={Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004}, notes={2004}, year={2004}, pages={380 - 384 }, abstract={This work introduces a novel technique for dynamic particle swarm optimization (DPSO) using adaptive critic designs. The adaptation between global and local search in an optimization algorithm is critical for optimization problems especially in a dyn..... } } @inproceedings{ieeebib185, title={ An improved particle swarm optimization algorithm with disturbance}, author = {Wei Jian and Yuncan Xue and Jixin Qian}, booktitle={2004 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 6, 10-13 Oct. 2004}, year={2004}, pages={5900 - 5904 vol.6}, abstract={The impacts of constant parameters on particle swarm optimization are discussed. A velocity or position disturbance is introduced to prevent premature phenomenon of the original algorithm. A valve is introduced and the selection criteria are discusse..... } } @inproceedings{ieeebib186, title={ A discrete particle swarm optimization algorithm for phylogenetic tree reconstruction}, author = {Hui-Ying Lv and Wen-Gang Zhou and Chun-Guang Zhou}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2650 - 2654 vol.4 }, abstract={The similarity of molecular mechanisms of the organisms that have been studied strongly suggests that all organisms of Earth had a common ancestor. Thus any set of species is related, and the relationship is called a phylogeny. Usually a phylogenetic..... } } @inproceedings{ieeebib187, title={ A fast algorithm for image analogy using particle swarm optimization}, author = {Yan Zhang and Yu Meng and Wen-Hui Li and Yun-Jie Pang}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 7, 26-29 Aug. 2004}, year={2004}, pages={4043 - 4048 vol.7 }, abstract={This work employs particle swarm optimization (PSO) based texture synthesis approaches, it differs from the pixel-based texture synthesis method, in this way, and the synthesis speed is increased. We apply particle swarm optimization (PSO) to improve..... } } @inproceedings{ieeebib188, title={ The particle swarm optimization with division of work strategy}, author = {Quan-Sheng Dou and Chun-Guang Zhou}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2290 - 2295 vol.4 }, abstract={The particle swarm optimization (PSO) method was originally designed by Kennedy and Eberhart in 1995 and has been applied successfully to various optimization problems. The PSO idea is inspired by natural concepts such as fish schooling, bird flockin..... } } @inproceedings{ieeebib189, title={ Handling boundary constraints for numerical optimization by particle swarm flying in periodic search space}, author = {Wen-Jun Zhang and Xiao-Feng Xie and De-Chun Bi}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 2, 19-23 June 2004}, year={2004}, pages={2307 - 2311 Vol.2 }, abstract={The periodic mode is analyzed together with two conventional boundary handling modes for particle swarm. By providing an infinite space that comprises periodic copies of original search space, it avoids possible disorganizing of particle swarm that i..... } } @inproceedings{ieeebib19, title={ Particle swarm optimization: developments, applications and resources}, author = {Eberhart and Yuhui Shi}, booktitle={Proceedings of the 2001 Congress on Evolutionary Computation, 2001}, notes={Volume 1, 27-30 May 2001}, year={2001}, pages={81 - 86 vol. 1 }, abstract={This paper focuses on the engineering and computer science aspects of developments, applications, and resources related to particle swarm optimization. Developments in the particle swarm algorithm since its origin in 1995 are reviewed. Included are b..... } } @inproceedings{ieeebib190, title={ Supervisor-student model in particle swarm optimization}, author = {Yu Liu and Zheng Qin and Xingshi He}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={542 - 547 Vol.1 }, abstract={Particle swarm optimization (PSO) algorithms have exhibited good performance on well-known numerical test problems. In this paper, we propose a supervisor-student model in particle swarm optimization (SSM-PSO) that may further reduce computational co..... } } @inproceedings{ieeebib191, title={ The application of particle swarm optimization to adaptive IIR phase equalization}, author = {D.J. Krusienski and W.K. Jenkins}, booktitle={Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '04)}, notes={Volume 2, 17-21 May 2004}, year={2004}, pages={ii - 693-6 vol.2}, abstract={This paper investigates the application of particle swarm optimization techniques to infinite impulse response (IIR) adaptive phase equalizers. Particle swarm optimization (PSO) is similar to the genetic algorithm (GA) in that it utilizes a populatio..... } } @inproceedings{ieeebib192, title={ Particle swarm optimization algorithm and its application to clustering analysis}, author = {Ching-Yi Chen and Fun Ye}, booktitle={2004 IEEE International Conference on Networking, Sensing and Control}, notes={Volume 2, 2004}, year={2004}, pages={789 - 794 Vol.2}, abstract={Clustering analysis is applied generally to pattern recognition, color quantization and image classification. It can help the user to distinguish the structure of data and simplify the complexity of data from mass information. The user can understand..... } } @inproceedings{ieeebib193, title={ Probability and dynamics in the particle swarm}, author = {J. Kennedy}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={340 - 347 Vol.1 }, abstract={This paper investigates emulation of the particle swarm algorithm through the use of random number generators. The dynamics of the particle swarm seem to influence its performance. Alternative algorithms are investigated...... } } @inproceedings{ieeebib194, title={ RF circuit synthesis using particle swarm optimization}, author = {Jinho Park and D.J. Allstot}, booktitle={Proceedings of the 2004 International Symposium on Circuits and Systems, 2004. ISCAS '04}, notes={Volume 5, 23-26 May 2004}, year={2004}, pages={V-93 - V-96 Vol.5 }, abstract={A parasitic-aware design methodology based on particle swarm optimization is presented. It is shown that parasitic-aware design using the particle swarm rather than using the simulated annealing heuristic gives better performance. The proposed parasi..... } } @inproceedings{ieeebib195, title={ A constraint-handling mechanism for particle swarm optimization}, author = {G.T. Pulido and C.A.C. Coello}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 2, 19-23 June 2004}, year={2004}, pages={1396 - 1403 Vol.2 }, abstract={This work presents a simple mechanism to handle constraints with a particle swarm optimization algorithm. Our proposal uses a simple criterion based on closeness of a particle to the feasible region in order to select a leader. Additionally, our algo..... } } @inproceedings{ieeebib196, title={ Particle swarm optimization and neural network application for QSAR}, author = {Z. Wang and G.L. Durst and R.C. Eberhart and D.B. Boyd and Z.B. Miled}, booktitle={Proceedings of the 18th International Parallel and Distributed Processing Symposium, 2004. }, notes={26-30 April 2004}, year={2004}, pages={194 }, abstract={Summary form only given. A successful approach to building QSAR models was proposed by other researchers. It uses binary particle swarm optimization (BPSO) for feature selection in the first stage, and a back propagation neural network in the second ..... } } @inproceedings{ieeebib197, title={ Adaptive filtering via particle swarm optimization}, author = {D.J. Krusienski and W.K. Jenkins}, booktitle={Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, 2003}, notes={Volume 1, 9-12 Nov. 2003}, year={2003}, pages={571 - 575 Vol.1 }, abstract={This paper introduces the application of particle swarm optimization techniques to generalized adaptive nonlinear and recursive filter structures. Particle swarm optimization (PSO) is a population based optimization algorithm, similar to the genetic ..... } } @inproceedings{ieeebib198, title={ Adaptive particle swarm optimisation for high-dimensional highly convex search spaces}, author = {D. Tsou and C. MacNish}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 2, 8-12 Dec. 2003}, year={2003}, pages={783 - 789 Vol.2 }, abstract={The particle swarm optimisation (PSO) algorithm has been established as a useful global optimisation algorithm for multidimensional search spaces. A practical example is its success in training feed-forward neural networks. Such successes, however, m..... } } @inproceedings{ieeebib199, title={ Optimisation of valve timing events of internal combustion engines with particle swarm optimisation}, author = {A. Ratnaweera and H.C. Watson and S.K. Halgamuge}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 4, 8-12 Dec. 2003}, year={2003}, pages={2411 - 2418 Vol.4 }, abstract={The best combination of valve timing events along with three dominant engine operating parameters was observed for optimum performance of an internal combustion spark ignition (ICSI) engine with particle swarm optimisation (PSO) method. A thermodynam..... } } @inproceedings{ieeebib2, title={ Multiple sectors, multi function, multi radar dwell time management using particle swarm optimization (M3RTM)}, author = {K. Veeramachaneni and L.A. Osadciw}, booktitle={2006 IEEE Conference on Radar}, date={24-27 April 2006}, pages={7 pp.}, year={2006}, abstract={In this paper a particle swarm optimization algorithm based approach is presented for dwell time management of multiple multi function radars monitoring multiple sectors. Each radar can perform two functions, which are normal surveillance (NS) or sea..... } } @article{ieeebibJ20, title={ Multimodal function optimization based on particle swarm optimization}, author={Jang-Ho Seo and Chang-Hwan Im and Chang-Geun Heo and Jae-Kwang Kim and Hyun-Kyo Jung and Cheol-Gyun Lee}, journal={IEEE Transactions on Magnetics}, volume= 42, issue= 4, date={ April 2006}, pages={1095 - 1098 }, year={2006}, abstract={In this paper, a new algorithm for the multimodal function optimization is proposed, based on the particle swarm optimization (PSO). A new method, named the multigrouped particle swarm optimization (MGPSO), keeps basic concepts of the PSO, and, thus,..... } } @inproceedings{ieeebib200, title={ Particle swarm inspired evolutionary algorithm (PS-EA) for multiobjective optimization problems}, author = {Dipti Srinivasan and T.H. Seow}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 4, 8-12 Dec. 2003}, year={2003}, pages={2292 - 2297 Vol.4 }, abstract={We describe particle swarm inspired evolutionary algorithm (PS-EA), which is a hybridized evolutionary algorithm (EA) combining the concepts of EA and particle swarm theory. PS-EA is developed in aim to extend PSO algorithm to effectively search in m..... } } @inproceedings{ieeebib201, title={ Particle swarm optimization for worst case tolerance design}, author = {G. Steiner and D. Watzenig}, booktitle={2003 IEEE International Conference on Industrial Technology}, notes={Volume 1, 10-12 Dec. 2003}, year={2003}, pages={78 - 82 Vol.1}, abstract={Worst case tolerance analysis is a major subtask in modern industrial electronics. Recently, the demands on industrial products like production costs or probability of failure have become more and more important in order to be competitive in business..... } } @inproceedings{ieeebib202, title={ Particle swarm optimization solution to emission and economic dispatch problem}, author = {A.I.S. Kumar and K. Dhanushkodi and J.J. Kumar and C.K.C. Paul}, booktitle={TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region}, notes={Volume 1, 15-17 Oct. 2003}, year={2003}, pages={435 - 439 Vol.1 }, abstract={The paper presents an efficient and reliable particle swarm optimization (PSO) algorithm based technique for solving emission and economic dispatch (E\&ED) problems. The harmful ecological effects of the emission of particulate and gaseous pollutants ..... } } @inproceedings{ieeebib203, title={ Neighborhood topologies in fully-informed and best-of-neighborhood particle swarms}, author = {J. Kennedy and R. Mendes}, booktitle={Proceedings of the 2003 IEEE International Workshop on Soft Computing in Industrial Applications, 2003. SMCia/03}, notes={23-25 June 2003}, year={2003}, pages={45 - 50 }, abstract={We vary the way an individual in the particle swarm interacts with its neighbors. Performance depends on population topology as well as algorithm version...... } } @inproceedings{ieeebib204, title={ Particle swarm optimization with Gaussian mutation}, author = {N. Higashi and H. Iba}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={72 - 79}, abstract={In this paper we present particle swarm optimization with Gaussian mutation combining the idea of the particle swarm with concepts from evolutionary algorithms. This method combines the traditional velocity and position update rules with the ideas of..... } } @inproceedings{ieeebib205, title={ Traffic incident detection using particle swarm optimization}, author = {D. Srinivasan and Wee Hoon Loo and Ruey Long Cheu}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={144 - 151}, abstract={This paper proposes a new approach to automatic incident detection on traffic highways using particle swarm optimization (PSO). The rampant growth in traffic incidents, which is high cost incurring, has led to significant interest in the development ..... } } @inproceedings{ieeebib206, title={ EPSO-evolutionary particle swarm optimization, a new algorithm with applications in power systems}, author = {V. Miranda and N. Fonseca}, booktitle={Transmission and Distribution Conference and Exhibition 2002: Asia Pacific. IEEE/PES}, notes={Volume 2, 6-10 Oct. 2002}, year={2002}, pages={745 - 750 vol.2 }, abstract={This paper presents a new optimization model EPSO, evolutionary particle swarm optimization, inspired in both evolutionary algorithms and in particle swarm optimization algorithms. The fundamentals of the method are described, and an application to t..... } } @inproceedings{ieeebib207, title={ Enhancing the particle swarm optimizer via proper parameters selection}, author = {A. El-Gallad and M. El-Hawary and A. Sallam and A. Kalas}, booktitle={Canadian Conference on Electrical and Computer Engineering, 2002. IEEE CCECE 2002}, notes={Volume 2, 12-15 May 2002}, year={2002}, pages={792 - 797 vol.2 }, abstract={Unlike many other computational intelligence techniques, the particle swarm optimizer (PSO) has few parameters to tune. However, properly chosen values for these parameters can positively affect the accuracy of the obtained results as well as the tim..... } } @inproceedings{ieeebib208, title={ Multi-phase generalization of the particle swarm optimization algorithm}, author = {B. Al-kazemi and C.K. Mohan}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 1, 12-17 May 2002}, year={2002}, pages={489 - 494 }, abstract={Multi-phase particle swarm optimization is a new algorithm to be used for discrete and continuous problems. In this algorithm, different groups of particles have trajectories that proceed with differing goals in different phases of the algorithm. On ..... } } @inproceedings{ieeebib209, title={ Co-evolutionary particle swarm optimization to solve min-max problems}, author = {Yuhui Shi and R.A. Krohling}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1682 - 1687 }, abstract={A co-evolutionary particle swarm optimization (PSO) to solve constrained optimization problems is proposed. First, we introduce the augmented Lagrangian to transform a constrained optimization to a min-max problem with the saddle-point solution. Next..... } } @article{ieeebibJ21, title={ Comprehensive learning particle swarm optimizer for global optimization of multimodal functions}, author={J.J. Liang and A.K. Qin and P.N. Suganthan and S. Baskar}, journal={IEEE Transactions on Evolutionary Computation}, volume= 10, issue= 3, date={ June 2006}, pages={281 - 295 }, year={2006}, abstract={This paper presents a variant of particle swarm optimizers (PSOs) that we call the comprehensive learning particle swarm optimizer (CLPSO), which uses a novel learning strategy whereby all other particles' historical best information is used to updat..... } } @inproceedings{ieeebib210, title={ Training product unit networks using cooperative particle swarm optimisers}, author = {F. van den Bergh A.P. Engelbrecht}, booktitle={Proceedings of the International Joint Conference on Neural Networks, 2001. IJCNN '01}, notes={Volume 1, 15-19 July 2001}, year={2001}, pages={126 - 131 vol.1 }, abstract={The cooperative particle swarm optimiser (CPSO) is a variant of the particle swarm optimiser (PSO) that splits the problem vector, for example a neural network weight vector, across several swarms. The paper investigates the influence that the number..... } } @inproceedings{ieeebib211, title={ Human tremor analysis using particle swarm optimization}, author = {R.C. Eberhart and Xiaohui Hu}, booktitle={Proceedings of the 1999 Congress on Evolutionary Computation, 1999. CEC 99}, notes={Volume 3, 6-9 July 1999}, year={1999}, pages={ }, abstract={The paper presents methods for the analysis of human tremor using particle swarm optimization. Two forms of human tremor are addressed: essential tremor and Parkinson's disease. Particle swarm optimization is used to evolve a neural network that dist..... } } @inproceedings{ieeebib212, title={ Using selection to improve particle swarm optimization}, author = {P.J. Angeline}, booktitle={The 1998 IEEE International Conference on Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence.}, notes={4-9 May 1998}, year={1998}, pages={84 - 89}, abstract={This paper describes a evolutionary optimization algorithm that is a hybrid based on the particle swarm algorithm but with the addition of a standard selection mechanism from evolutionary computations. A comparison is performed between the hybrid swa..... } } @inproceedings{ieeebib213, title={ A discrete binary version of the particle swarm algorithm}, author = {J. Kennedy and R.C. Eberhart}, booktitle={1997 IEEE International Conference on Systems, Man, and Cybernetics, 1997. 'Computational Cybernetics and Simulation'.}, notes={Volume 5, 12-15 Oct. 1997}, year={1997}, pages={4104 - 4108 vol.5}, abstract={The particle swarm algorithm adjusts the trajectories of a population of particles through a problem space on the basis of information about each particle's previous best performance and the best previous performance of its neighbors. P..... } } @inproceedings{ieeebib214, title={ A new optimizer using particle swarm theory}, author = {R. Eberhart and J. Kennedy}, booktitle={Proceedings of the Sixth International Symposium on Micro Machine and Human Science, 1995. MHS '95.}, notes={4-6 Oct. 1995}, year={1995}, pages={39 - 43 }, abstract={The optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm. Benchmark testing of both paradigms is descr..... } } @inproceedings{ieeebib215, title={ Particle swarm optimization}, author = {J. Kennedy and R. Eberhart}, booktitle={Proceedings of the IEEE International Conference on Neural Networks, 1995}, notes={Volume 4, 27 Nov.-1 Dec. 1995}, year={1995}, pages={1942 - 1948 vol.4}, abstract={A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is des..... } } @inproceedings{ieeebib216, title={ Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data}, author = {Rui Xu and Georgios C. Anagnostopoulos and Donald C. Wunsch}, booktitle={IEEE/ACM Transactions on Computational Biology and Bioinformatics}, notes={Volume 4, Issue 1, Jan.-March 2007}, year={2007}, pages={65 - 77 }, abstract={It is crucial for cancer diagnosis and treatment to accurately identify the site of origin of a tumor. With the emergence and rapid advancement of DNA microarray technologies, constructing gene expression profiles for different cancer types has alrea..... } } @inproceedings{ieeebib217, title={ Particle swarm optimization for the design of low-dispersion fiber Bragg gratings}, author = {S. Baskar and R.T. Zheng and A. Alphones and N.Q. Ngo and P.N. Suganthan}, booktitle={Photonics Technology Letters, IEEE}, notes={Volume 17, Issue 3, Mar 2005}, year={2005}, pages={615 - 617 }, abstract={We propose a novel formulation of the objective function for the design of fiber Bragg grating (FBG)-based filters with respect to the given design specifications, instead of matching the desired magnitude and phase responses of the filter at each wa..... } } @inproceedings{ieeebib218, title={ A hybrid boundary condition for robust particle swarm optimization}, author = {T. Huang and A.S. Mohan}, booktitle={Antennas and Wireless Propagation Letters}, notes={Volume 4, 2005}, year={2005}, pages={112 - 117 }, abstract={The particle swarm optimization (PSO) technique is a powerful stochastic evolutionary algorithm that can be used to find the global optimum solution in a complex search space. However, it has been observed that there is a great variation in its perfo..... } } @article{ieeebibJ219, title={ Quantum Particle Swarm Optimization for Electromagnetics}, author={S.M. Mikki and A.A. Kishk}, journal={IEEE Transactions on Antennas and Propagation}, volume= 54, issue= 10, date={ Oct. 2006}, pages={2764 - 2775 }, year={2006}, abstract={A new particle swarm optimization (PSO) technique for electromagnetic applications is proposed. The method is based on quantum mechanics rather than the Newtonian rules assumed in all previous versions of PSO, which we refer to as classical PSO. A ge..... } } @inproceedings{ieeebib22, title={ Particle Swarm Assisted Incremental Evolution Strategy for Function Optimization}, author = {Wenting Mo and Sheng-Uei Guan}, booktitle={2006 IEEE Conference on Cybernetics and Intelligent Systems}, note={June 2006}, year={2006}, pages={1 - 6 }, abstract={This paper presents a new evolutionary approach for function optimization problems particle swarm assisted incremental evolution strategy (PIES). Two strategies are proposed. One is incremental optimization that the whole evolution consists of severa..... } } @article{ieeebibJ220, title={ Determining generator contributions to transmission system using parallel vector evaluated particle swarm optimization}, author={J.G. Vlachogiannis and K.Y. Lee}, journal={IEEE Transactions on Power Systems}, volume= 20, issue= 4, date={ Nov. 2005}, pages={1765 - 1774 }, year={2005}, abstract={In this paper, the generator contributions to the transmission system are determined by an evolutionary computation technique. Evaluating the contributions of generators to the power flows in transmission lines is formulated as a multiobjective optim..... } } @article{ieeebibJ221, title={ A hybrid particle swarm optimization applied to loss power minimization}, author={A.A.A. Esmin and G. Lambert-Torres and A.C. Zambroni de Souza}, journal={IEEE Transactions on Power Systems}, volume= 20, issue= 2, date={ May 2005}, pages={859 - 866 }, year={2005}, abstract={This paper presents a particle swarm optimization (PSO) as a tool for loss reduction study. This issue can be formulated as a nonlinear optimization problem. The proposed application consists of using a developed optimal power flow based on loss mini..... } } @article{ieeebibJ222, title={ A particle swarm optimization to identifying the ARMAX model for short-term load forecasting}, author={Chao-Ming Huang and Chi-Jen Huang and Ming-Li Wang}, journal={IEEE Transactions on Power Systems}, volume= 20, issue= 2, date={ May 2005}, pages={1126 - 1133 }, year={2005}, abstract={In this paper, a new particle swarm optimization (PSO) approach to identifying the autoregressive moving average with exogenous variable (ARMAX) model for one-day to one-week ahead hourly load forecasts was proposed. Owing to the inherent nonlinear c..... } } @article{ieeebibJ223, title={ A particle swarm optimization approach for optimum design of PID controller in AVR system}, author={Zwe-Lee Gaing}, journal={IEEE Transactions on Energy Conversion}, volume= 19, issue= 2, date={ June 2004}, pages={384 - 391 }, year={2004}, abstract={In this paper, a novel design method for determining the optimal proportional-integral-derivative (PID) controller parameters of an AVR system using the particle swarm optimization (PSO) algorithm is presented. This paper demonstrated in detail how t..... } } @article{ieeebibJ224, title={ A hierarchical particle swarm optimizer and its adaptive variant}, author={S. Janson and M. Middendorf}, journal={IEEE Transactions on Systems, Man and Cybernetics, Part B}, volume= 35, issue= 6, date={ Dec. 2005}, pages={1272 - 1282 }, year={2005}, abstract={A hierarchical version of the particle swarm optimization (PSO) metaheuristic is introduced in this paper. In the new method called H-PSO, the particles are arranged in a dynamic hierarchy that is used to define a neighborhood structure. Depending on..... } } @article{ieeebibJ225, title={ Design of a multiband CPW-fed monopole antenna using a particle swarm optimization approach}, author={Wen-Chung Liu}, journal={IEEE Transactions on Antennas and Propagation}, volume= 53, issue= 10, date={ Oct. 2005}, pages={3273 - 3279 }, year={2005}, abstract={A novel coplanar waveguide fed planar monopole antenna for multiband operation is presented in this paper. By embedding appropriate slits into the 50 /spl Omega/ feeding line, good impedance matching for multiresonant mode is obtained. The evolutiona..... } } @article{ieeebibJ226, title={ On the computation of all global minimizers through particle swarm optimization}, author={K.E. Parsopoulos and M.N. Vrahatis}, journal={IEEE Transactions on Evolutionary Computation}, volume= 8, issue= 3, date={ June 2004}, pages={211 - 224 }, year={2004}, abstract={This paper presents approaches for effectively computing all global minimizers of an objective function. The approaches include transformations of the objective function through the recently proposed deflection and stretching techniques, as well as a..... } } @article{ieeebibJ227, title={ Linear Array Geometry Synthesis With Minimum Sidelobe Level and Null Control Using Particle Swarm Optimization}, author={M.M. Khodier and C.G. Christodoulou}, journal={IEEE Transactions on Antennas and Propagation}, volume= 53, issue= 8, date={}, part2={ Aug. 2005 Page(s):2674 - 2679 }, year=2005, abstract={This paper describes the synthesis method of linear array geometry with minimum sidelobe level and null control using the particle swarm optimization (PSO) algorithm. The PSO algorithm is a newly discovered, high-performance evolutionary algorithm ca..... } } @article{ieeebibJ228, title={ A particle swarm optimization-based method for multiobjective design optimizations}, author={S.L. Ho and Shiyou Yang and Guangzheng Ni and E.W.C. Lo and H.C. Wong}, journal={IEEE Transactions on Magnetics}, volume= 41, issue= 5, date={ May 2005}, pages={1756 - 1759 }, year={2005}, abstract={A particle swarm optimization (PSO) based algorithm for finding the Pareto solutions of multiobjective design problems is proposed. To enhance the global searching ability of the available PSOs, a novel formula for updating the particles' velocity an..... } } @article{ieeebibJ229, title={ Computational approach based on a particle swarm optimizer for microwave imaging of two-dimensional dielectric scatterers}, author={M. Donelli and A. Massa}, journal={IEEE Transactions on Microwave Theory and Techniques}, volume= 53, issue= 5, date={ May 2005}, pages={1761 - 1776 }, year={2005}, abstract={A computational approach based on an innovative stochastic algorithm, namely, the particle swarm optimizer (PSO), is proposed for the solution of the inverse-scattering problem arising in microwave-imaging applications. The original inverse-scatterin..... } } @inproceedings{ieeebib23, title={ Application of Varying Population Size Particle Swarm Optimization Algorithm to AGC of Power Systems}, author = {Fei Ma and Xue-bo Chen}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3310 - 3314 }, abstract={An effective method of making tradeoff between the optimize precision and optimize speed for load frequency control in the automatic generation control, which can improve the calculating process of particle swarm algorithm is presented in this paper...... } } @inproceedings{ieeebib230, title={ Particle swarm optimisation for Pareto optimal solutions in electromagnetic shape design}, author = {U. Baumgartner and C. Magele and K. Preis and W. Renhart}, booktitle={Science, Measurement and Technology, IEE Proceedings-}, notes={Volume 151, Issue 6, 4 Nov. 2004}, year={2004}, pages={499 - 502 }, abstract={Real world optimisation problems require the minimisation/maximisation of objectives that are often in conflict with one another. These problems (multi-objective optimisation problems, vector optimisation problems) are in general treated by using wei.....} } @inproceedings{ieeebib231, title={ PSOSA: An Optimized Particle Swarm Technique for Solving the Urban Planning Problem}, author = {W. Al-Hassan and M.B. Fayek and S.I. Shaheen}, booktitle={The 2006 International Conference on Computer Engineering and Systems}, notes={Nov. 2006}, year={2006}, pages={401 - 405 }, abstract={This paper introduces an optimized particle swarm technique (PSOSA) that uses simulated annealing for optimizing the inertia weight. To study the performance of the proposed technique, it has been applied on the urban planning problem involving a mul..... } } @inproceedings{ieeebib232, title={ Three Sub-Swarm Discrete Particle Swarm Optimization Algorithm}, author = {Yufa Xu and Guochu Chen and Jinshou Yu}, booktitle={2006 IEEE International Conference on Information Acquisition}, notes={Aug. 2006}, year={2006}, pages={1224 - 1228}, abstract={Three sub-swarm discrete particle swarm optimization algorithm (THSDPSO) is proposed. The new algorithm assumes that all particles are divided into three sub-swarms. One sub-swarm flies toward the global best position. The second sub-swarm flies in t..... } } @inproceedings{ieeebib233, title={ Using Particle Swarm Optimisation for Elastic Bunch Graph Matching to Recognise Faces}, author = {R. Senaratne and S. Halgamuge}, booktitle={TENCON 2005 2005 IEEE Region 10}, notes={Nov. 2005}, year={2005}, pages={1 - 6 }, abstract={A new approach to face recognition, where Elastic Bunch Graph Matching technique optimised with Particle Swarm Optimisation is proposed in this paper. It is a fully automatic algorithm and can be used for databases where only one image per person is ..... } } @inproceedings{ieeebib234, title={ General Particle Swarm Optimization Based on Simulated Annealing for Multi-Specification One-dimensional Cutting Stock Problem}, author = {Xianjun Shen and Yuanxiang Li and Zhifeng Dai and Bojin Zheng}, booktitle={2006 International Conference on Computational Intelligence and Security}, notes={Volume 1, Nov. 2006}, year={2006}, pages={461 - 464 }, abstract={In this paper a general particle swarm optimization based on SA algorithm (SA-GPSO) for the solution to multi-specification one-dimensional cutting stock problem is proposed. Due to the limitation of its velocity-displacement search model, particle s..... } } @inproceedings{ieeebib235, title={ Particle Swarm Optimization with Escape Velocity}, author = {Xiuli Wang and Yongji Wang and Haitao Zeng and Hui Zhou}, booktitle={2006 International Conference on Computational Intelligence and Security}, notes={Volume 1, Nov. 2006}, year={2006}, pages={457 - 460 }, abstract={This paper presents a model of Particle Swarm Optimization with Escape Velocity (EVPSO) in order to overcome premature convergence in the basic Particle Swarm Optimization (PSO). The EVPSO model equips particles with the escape velocity to avoid them..... } } @inproceedings{ieeebib236, title={ A Modified Particle Swarm Optimization Algorithm}, author = {Jiang Yan and Hu Tiesong and Huang Chongchao and Wu Xianing}, booktitle={2006 International Conference on Computational Intelligence and Security}, notes={Volume 1, Nov. 2006}, year={2006}, pages={421 - 424 }, abstract={A shuffled complex evolution of particle swarm optimization algorithm called SCE-PSO is introduced in this paper. In SCE-PSO, a population of points sampled randomly from the feasible space is partitioned into several complexes, each of which is perm..... } } @inproceedings{ieeebib237, title={ Adaptive Particle Swarm Optimization Guided by Acceleration Information}, author = {Jianchao Zeng and Jing Jie and Jianxiu Hu}, booktitle={2006 International Conference on Computational Intelligence and Security}, notes={Volume 1, Nov. 2006}, year={2006}, pages={351 - 355 }, abstract={In order to improve the global convergent ability of the standard particle swarm optimization(SPSO), the paper develops a new version of particle swarm optimization guided by the acceleration information(AGPSO). Firstly, the paper introduces the conc..... } } @inproceedings{ieeebib238, title={ Feedback Linearization of an Electrostatic Actuator by Particle Swarm Optimization}, author = {D.J. Broderick and J.Y. Hung}, booktitle={2006 IEEE International Symposium on Industrial Electronics}, notes={Volume 1, July 2006}, year={2006}, pages={289 - 294 }, abstract={A method of searching for an input to state linearizing controller is presented. The problem of finding the appropriate weights of the control law's terms is treated as an optimization problem. Given the highly nonlinear surfaces that are likely to b..... } } @inproceedings{ieeebib239, title={ An Improved Particle Swarm Optimizer for Truss Structure Optimization}, author = {Lijuan Li and Zhibin Huang and Feng Liu}, booktitle={2006 International Conference on Computational Intelligence and Security}, notes={Volume 1, Nov. 2006}, year={2006}, pages={924 - 928 }, abstract={This paper presents an improved particle swarm optimizer (IPSO) for solving truss structure optimization problems. The algorithm is based on the particle swarm optimizer with passive congregation (PSOPC) and a harmony search (HS) scheme. It handles t..... } } @inproceedings{ieeebib24, title={ A Novel Real Number Encoding Method of Particle Swarm Optimization for Vehicle Routing Problem}, author = {Bin Wu and Wanliang Wang and Yanwei Zhao and Xinli Xu and Fengyu Yang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3271 - 3275 }, abstract={Vehicle Routing Problem is a well-known NP problem, many heuristic algorithms, such as Genetic algorithm, Simulated Annealing algorithm is applied in the problem. Particle swarm optimization (PSO) is a new evolutionary computation technique. Although..... } } @inproceedings{ieeebib240, title={ Reserve-Constrained Multiarea Environmental/Economic Dispatch Using Enhanced Particle Swarm Optimization}, author = {L. Wang and C. Singh}, booktitle={Systems and Information Engineering Design Symposium, 2006 IEEE}, notes={April 2006}, year={2006}, pages={96 - 100 }, abstract={Multiarea economic dispatch (MAED) is developed from the basic economic dispatch (ED) problem, which considers the optimal power dispatch of multiple areas in terms of operational costs. In this study, the concept of MAED is further extended into mul..... } } @inproceedings{ieeebib241, title={ Self-tuning of PID Parameters Based on the Modified Particle Swarm Optimization}, author = {Yuncan Xue and Haibin Zhao and Qiwen Yang}, booktitle={2006 IEEE International Conference on Industrial Informatics}, notes={Aug. 2006}, year={2006}, pages={870 - 873}, abstract={To overcome premature of standard particle swarm optimization (SPSO) algorithm, a modified particle swarm optimization (MPSO) based on partial particle moving direction changing was proposed. It holds on the proprieties of simple structure, fast conv..... } } @inproceedings{ieeebib242, title={ Input Selection Using Binary Particle Swarm Optimization}, author = {T. Amonchanchaigul and W. Kreesuradej}, booktitle={International Conference on Computational Intelligence for Modelling, Control and Automation, 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce}, notes={Nov. 2006}, year={2006}, pages={159 - 159 }, abstract={Nowadays, multi-layer feed forward networks are often used for modeling complex relationships between the data sets. And if we can choose only the important data from the training sets, it will make the networks less size and can save more time. Beca..... } } @inproceedings{ieeebib243, title={ Local Parameters Particle Swarm Optimization}, author = {P. Tawdross and A. Konig}, booktitle={Sixth International Conference on Hybrid Intelligent Systems, 2006. HIS '06}, notes={Dec. 2006}, year={2006}, pages={52 - 52 }, abstract={Recently the particle swarm optimization (PSO) has been used in many engineering applications, which operate in dynamic environment and has proved its competitiveness over genetic algorithmin many natural number approaches. In the state of the art, i..... } } @inproceedings{ieeebib244, title={ Design of Two-Dimensional Recursive Filters by Using Quantum-Behaved Particle Swarm Optimization}, author = {Wei Fang and Jun Sun and Wenbo Xu}, booktitle={International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2006. IIH-MSP '06}, notes={Dec. 2006}, year={2006}, pages={240 - 243 }, abstract={A novel algorithm, named Quantum-behaved particle swarm optimization (QPSO) proposed by us previously is introduced in the design of twodimensional (2-D) recursive digital filters. The design of the 2-D filters is reduced to a constrained minimizatio..... } } @inproceedings{ieeebib245, title={ A Modified Particle Swarm Algorithm Combined with Fuzzy Neural Network with Application to Financial Risk Early Warning}, author = {Fu-yuan Huang and Rong-jun Li and Han-xia Liu and Rui Li}, booktitle={IEEE Asia-Pacific Conference on Services Computing, 2006. APSCC '06}, notes={Dec. 2006}, year={2006}, pages={168 - 173 }, abstract={Particle Swarm Optimization (PSO) algorithm and Fuzzy Neural Network (FNN) system has been widely used to solve complex decision making problems in practice. However, both of them more or less suffer from the slow convergence and occasionally involve..... } } @inproceedings{ieeebib246, title={ The Maximum Variance Between Clusters Method of Image Segmentation Based on Particle Swarm Optimization}, author = {Jian-Ming Li and Zhong-Xian Chi and Li-Qiang Yu and Feng Zhang and Qiao-Qiao Jiang}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={3765 - 3769 }, abstract={This essay proposes a maximum variance between clusters method of Image Segmentation (OTSU) Based on PSO. The method in this paper makes use of particle swarm algorism and achieves a great acceleration to the traditional OTSU. On that basis, we also ..... } } @inproceedings{ieeebib247, title={ Distribution Network Reconfiguration Basedl on Modified Particle Swarm Optimization Algorithm}, author = {Cui-Ru Wang and Yun-E Zhang}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={2076 - 2080 }, abstract={As a non-liner optimal problem, distribution network reconfiguration (DNR) impacts on economic benefit of power system greatly. In this paper, a modified particle swarm algorithm (MPSO) has been presented to solve the complex optimization problem. In..... } } @inproceedings{ieeebib248, title={ Formalization Description and Instance Research on Particle Swarm Optimization Algorithm}, author = {Lei Wang and Qi Kang and Hui Xiao and Qi-di Wu}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={963 - 968 }, abstract={Formalization description of particle swarm optimization algorithm is proposed based on the collectivity mode framework of swarm intelligence in this paper. As a specific case, a modified particle swarm optimization algorithm is brought forward in fo..... } } @inproceedings{ieeebib249, title={ Particle Swarm Optimization based Defensive Islanding of Large Scale Power System}, author = {Wenxin Liu and D.A. Cartes and G.K. Venayagamoorthy}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={1719 - 1725 }, abstract={Defensive islanding is an efficient way to avoid catastrophic failures and wide area blackouts. Power system splitting especially for large scale power systems is a combinatorial explosion problem. Thus, it is very difficult to find an optimal soluti..... } } @inproceedings{ieeebib25, title={ The Research on a Novel Geometric Constraint Solver}, author = {Chunhong Cao and Bin Zhang and Xiaolin Li and Limin Wang and Wenhui Li}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3504 - 3508 }, abstract={When transferring the geometric constraint equation group into the optimization model, we need a method to jump out of the local beat solution so that we can find a global best solution. Considering the speed and global capability, we adopt compound ..... } } @inproceedings{ieeebib250, title={ The Design of Neuro-Fuzzy Networks Using Particle Swarm Optimization and Recursive Singular Value Decomposition}, author = {Cheng-Jian Lin and Shang-Jin Hong and Chi-Yung Lee}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={2887 - 2893 }, abstract={In this paper, a neuro-fuzzy network with novel hybrid learning algorithm is proposed. The novel hybrid learning algorithm is based on the fuzzy entropy clustering (FEC), the modified particle swarm optimization (MPSO), and the recursive singular val..... } } @inproceedings{ieeebib251, title={ Nonlinear System Identification Based on B-Spline Neural Network and Modified Particle Swarm Optimization}, author = {L. dos Santos Coelho and R.A. Krohling}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={3748 - 3753 }, abstract={Artificial neural networks, in particular, feedforward multilayer networks and basis function networks, have gradually established themselves as a usual tool in approximating complex nonlinear systems. B-spline networks, a type of basis function neur..... } } @inproceedings{ieeebib252, title={ Optimum VAr sizing \& allocation using particle swarm optimization}, author = {A.A. El-Dib and H.K.M. Youssef and M.M. El-Metwally and Z. Osman}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={8 pp. }, abstract={This paper proposes a new solution technique for finding the optimum location and sizing of the shunt compensation devices in transmission system. This problem is not important only for improving the voltage profile but also for increasing the stabil..... } } @inproceedings{ieeebib253, title={ A modified particle swarm optimization algorithm for adaptive filtering}, author = {D.J. Krusienski and W.K. Jenkins}, booktitle={2006 IEEE International Symposium on Circuits and Systems, 2006. ISCAS 2006. Proceedings}, notes={21-24 May 2006}, year={2006}, pages={4 pp. }, abstract={Recently particle swarm optimization (PSO) has been studied for use in adaptive filtering problems where the mean squared error (MSE) surface is ill-conditioned. Although the swarm generally converges to a limit point, when the population of the swar..... } } @inproceedings{ieeebib254, title={ Congestion management based on particle swarm optimization}, author = {Zhi xu Chen and Li zi Zhang and Jun Shu}, booktitle={Power Engineering Conference, 2005. IPEC 2005. The 7th International}, notes={29 Nov.-2 Dec. 2005}, year={2005}, pages={1019 - 1023 Vol. 2 }, abstract={After analyzing the regulation of North East China electricity market and the constraint of safe operation of unit and transmission grid, this paper proposes a congestion management model that is appropriate for power pool. PSO (particle swarm optimi..... )} } @inproceedings{ieeebib255, title={ The Application of Neural Network Based on Particle Swarm Optimization in Pattern Recognition of Flatness Signal}, author = {Jianchang Liu and Yingying Chen}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6592 - 6595 }, abstract={In order to improve the precision of flatness recognition of strip, a new pattern recognizing approach of flatness was proposed. A kind of hybrid optimization strategy was used to train the neural network. That is to say, the weights were initialized..... } } @inproceedings{ieeebib256, title={ Control Policies in Multi-echelon Inventory Systems with Inventory-level-dependent Demand Rate}, author = {Dongyi Ma and Li Wang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6484 - 6488 }, abstract={This paper presented an inventory model of series system with inventory-level-dependent demand rate for multi-echelon inventory management policy, which was based on the concept of echelon stock. Then a relaxation-particle swarm optimization algorith..... } } @inproceedings{ieeebib257, title={ A Dual Similar Particle Swarm Optimization Algorithm for Job-Shop Scheduling with Penalty}, author = {Zhigang Lian and Xingsheng Gu and Bin Jiao}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7312 - 7316 }, abstract={In production, if manufacturer cannot deliver the goods on due-date, they will be punished according to earliness or tardiness and different products. According to these real situations, a Job-shop scheduling from restrictive due-date with penalty is..... } } @inproceedings{ieeebib258, title={ A Hybrid Particle Swarm Optimization(PSO) Algorithm Schemes for Integrated Process Planning and Production Scheduling}, author = {Fuqing Zhao and Aihong Zhu and Dongmei Yu and Yahong Yang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6772 - 6776 }, abstract={Process planning and production scheduling play important roles in manufacturing systems. Their roles are to ensure the availability of manufacturing resources needed to accomplish production tasks result from a demand forecast. In this paper, instea..... } } @inproceedings{ieeebib259, title={ Hybrid Particle Swarm Algorithm for Packing of Unequal Circles in A Larger Containing Circle}, author = {Yi-Chun Xu and Ren-Bin Xiao}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3381 - 3385 }, abstract={This paper describes an algorithm based on Particle Swarm Optimization (PSO) for the unequal circles packing problem. Three strategies are used to enlarge the searching space of PSO. First, the positions of particles are periodically reinitialized to..... } } @inproceedings{ieeebib26, title={ Lotto-type competitive learning with particle swarm features}, author = {A. Luk and S. Lien}, booktitle={2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05. Proceedings}, notes={Volume 3, 31 July-4 Aug. 2005}, year={2005}, pages={1517 - 1522 vol. 3 }, abstract={This correspondence describes our attempts of incorporating particle swarm features into competitive learning. We first reinterpret some of the symbols and notations used in particle swarm optimisation (PSO) algorithms in the light of competitive lea..... } } @inproceedings{ieeebib260, title={ An Improved Hybrid Particle Swarm Optimization Method for Distribution Network Planning}, author = {Xian Zhang and Jinsha Yuan and Xueming Yang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7470 - 7474 }, abstract={An improved hybrid particle swarm optimization for distribution network planning problem was proposed. The special mutation operator and the crossover operator among extremums of dynamic neighborhood were led. Another method called' trying its best t..... } } @inproceedings{ieeebib261, title={ Solving Optimal Power Flow Problems with Improved Particle Swarm Optimization}, author = {Bo Yang and Yunping Chen and Zunlian Zhao and Qiye Han}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7457 - 7461 }, abstract={The paper proposes an improved particle swarm optimization algorithm with preserving feasibility strategy and neighbor selection scheme for solving optimal power flow (OPF) problems. In the proposed algorithm, fitness function and constraints are han..... } } @inproceedings{ieeebib262, title={ Control a Novel Discrete Chaotic System through Particle Swarm Optimization}, author = {Fei Gao and Hengqing Tong}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3330 - 3334 }, abstract={To investigate the inherent chaotic phenomenon in genetic algorithms (GA), a novel chaos control approach through Particle Swarm Optimization (PSO) (CCPSO) with three main processes is proposed. Firstly it detects the dynamical behaviors of a new dis..... } } @inproceedings{ieeebib263, title={ A Novel Approach to Integrated Preventive Maintenance Planning and Production Scheduling for a Single Machine Using the Chaotic Particle Swarm Optimization Algorithm}, author = {Keping Leng and Ping Ren and Liqun Gao}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7816 - 7820 }, abstract={In this paper, integrated preventive maintenance planning and production scheduling for a single machine is formulated as a multi-objective mathematical optimization problem. Despite the inter-dependent relationship between them, production schedulin..... } } @inproceedings{ieeebib264, title={ Pattern Classification and Prediction of Water Quality by Neural Network with Particle Swarm Optimization}, author = {Chi Zhou and Liang Gao and Haibing Gao and Chuanyong Peng}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={2864 - 2868 }, abstract={Water pollution has posed a severe problem in modern society. Evaluation of water quality is a meaningful topic today. To identify the specific water category and predict the water quality in the future, a Particle Swarm Optimization (PSO) based Arti..... } } @inproceedings{ieeebib265, title={ Neural Network Predictive Control Based on Particle Swarm Optimization for Urban Expressway}, author = {Zhilin Lu and Bingquan Fan and Dongli Wang and Xiaoyang He}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={8606 - 8611 }, abstract={A neural network predictive control method based on particle swarm optimization (PSO) for the urban expressway is proposed. A series of serial-parallel structure radial basis function neural networks are used to identify the dynamic traffic flow mode..... } } @inproceedings{ieeebib266, title={ Self-Active Inertia Weight Strategy in Particle Swarm Optimization Algorithm}, author = {Guimin Chen and Zhengfeng Min and Jianyuan Jia and Xinbo Huang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3686 - 3689 }, abstract={Inertia weight is one of the most important parameters of particle swarm optimization (PSO) algorithm. We introduce s self-active inertia weight strategy, in which the inertia weight is updated according to the convergence rate of the search process ..... } } @inproceedings{ieeebib267, title={ Scroll Plate Optimization Based on Improved Genetic-Particle Swarm Optimization Algorithm}, author = {Bin Peng and Zhenquan Liu and Hongsheng Zhang and Li Zhang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3681 - 3685 }, abstract={The part optimization is very important for scroll compressor design. According to existing problems of current optimization algorithm and actual optimization problems, the improved genetic-particle swarm optimization algorithm (IGA-PSO) is proposed ..... } } @inproceedings{ieeebib268, title={ Natural Exponential Inertia Weight Strategy in Particle Swarm Optimization}, author = {Guimin Chen and Xinbo Huang and Jianyuan Jia and Zhengfeng Min}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3672 - 3675 }, abstract={Inertia weight is one of the most important parameters of particle swarm optimization (PSO) algorithm. Based on the basic idea of decreasing inertia weight (DIW), two strategies of natural exponential functions were proposed. Four different benchmark..... } } @inproceedings{ieeebib269, title={ Designing for RBF Networks Based on Particle Swarm Optimization and Regularized Orthogonal Least Squares}, author = {Ziwu Ren and Ye San}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={2825 - 2829 }, abstract={This paper presents a two-level learning method for designing radial basis function(RBF) networks based on particle swarm optimization(PSO) and regularized orthogonal least squares(ROLS), which is called ROLS-PSO method. The ROLS algorithm is employe..... } } @inproceedings{ieeebib27, title={ Particle swarms for drug design}, author = {W. Cedefto and D. Agraflotis}, booktitle={The 2005 IEEE Congress on Evolutionary Computation, 2005.}, notes={Volume 2, 2-5 Sept. 2005}, year={2005}, pages={1218 - 1225 Vol. 2}, abtract={The design of new drugs to prevent diseases and improve the quality life for people around the world is a challenge faced by the pharmaceutical industry on a daily basis. This has motivated scientists to find new chemoinformatics tools that can signi..... } } @inproceedings{ieeebib270, title={ A Particle Swarm Optimization Approach for PID Parameters in Hydraulic Servo Control System}, author = {Zou Jun and Fu Xin and Yang Huayong and Zhang Jianmin}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7725 - 7729 }, abstract={Particle swarm optimization(PSO), whose advantage is easy to implement, as an evolution algorithm, can search for optima quickly in multidimensional solution space. Based on PSO and classical PID controlling theory, an PSO-PID controller, using weigh..... } } @inproceedings{ieeebib271, title={ A Master-Slave Particle Swarm Optimization Algorithm for Solving Constrained Optimization Problems}, author = {Bo Yang and Yunping Chen and Zunlian Zhao and Qiye Han}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3208 - 3212 }, abstract={Penalty function based PSO converts constrained optimization problems into non-constrained optimization problems, but slow convergence and premature convergence easily happen because of inappropriate penalty coefficients. Modified PSO by tracking bes..... } } @inproceedings{ieeebib272, title={ An Improved Particle Swarm Optimization Based on Bacterial Chemotaxis}, author = {Ben Niu and Yunlong Zhu and Xiaoxian He and Xiangping Zeng}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3193 - 3197 }, abstract={Inspired by the phenomenon of chemotaxis in colonies of the bacteria, an improved particle swarm optimization (PSO) is presented by analogy to the way that bacteria react to chemo-attractants or chemo-repellents. The proposed algorithm (PSOBC) altern..... } } @inproceedings{ieeebib273, title={ Solving Weapon-Target Assignment Problem using Discrete Particle Swarm Optimization}, author = {Xiangping Zeng and Yunlong Zhu and Lin Nan and Kunyuan Hu and Ben Niu and Xiaoxian He}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3562 - 3565 }, abstract={This paper presents a discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem. The proposed algorithm sponges the advantages of PSO and GA. Originally the greedy searching strategy is introduced into DPSO in which ..... } } @inproceedings{ieeebib274, title={ Particle Swarm Optimization for Solving a Shooting Point}, author = {Dapeng Zhang and Fuli Wang and Dakuo He and Chunhui Zhao and Haifeng Sang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3538 - 3541 }, abstract={A shooting method is based on the solution of the ordinary differential equation for optimality that is obtained from Pontryagin's Maximum Principle. A shooting point must be approaching the perfect solution in order to assure algorithm's convergence..... } } @inproceedings{ieeebib275, title={ An Improved Two-Swarm Based Particle Swarm Optimization Algorithm}, author = {Ting Li and Xuzhi Lai and Min Wu}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3129 - 3133 }, abstract={Basic Particle Swarm Optimization (PSO) algorithm are susceptible to being trapped into local optimum and premature convergence happens. Inspired by the idea of genetic algorithm (GA), a new two-swarm based PSO algorithm (TSPSO) with roulette wheel s..... } } @inproceedings{ieeebib276, title={ Application of Velocity-Changeable Discrete Particle Swarm Optimization Algorithm for Blind Detection}, author = {Yite Xu and Dazhen Ye}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3509 - 3513 }, abstract={This paper extended the model of continue Particle Swarm Optimization (PSO) to Discrete Particle Swarm Optimization (DPSO) and gave its model on the basis of the analysis of conventional PSO, and, moreover, proposed a DPSO algorithm based on a veloci..... } } @inproceedings{ieeebib277, title={ The Application Study of Apple Color Grading by Particle Swarm Optimization Neural Networks}, author = {Haiyan Ji and Jinli Yuan}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={2651 - 2654 }, abstract={Color is an important index of fruit's external quality, and is studying object of fruit sorting. The apple surface images were acquired by computer vision technology, image's RGB format was converted to HIS format, and hue of every pixel was calcula..... } } @inproceedings{ieeebib278, title={ Application of Multiobjective Particle Swarm Optimization in Missile Effectiveness Optimization}, author = {Jia Xu and Shaojun Li and Feng Qian}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3499 - 3503 }, abstract={Pointing to the diversity measurement of Pareto solutions in particle swarm optimization algorithm, the maximin fitness function including additional warp is put forward. This algorithm named IMPSO has some very desirable properties with regard to mu..... } } @inproceedings{ieeebib279, title={ Research on Conflict Resolution Method based on Particle Swarm Optimization in Collaborative Design}, author = {Li Zhang and Xinyu Shao and Chi Zhou and Liang Gao}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3451 - 3455 }, abstract={The degree of cooperation and level of experts become the crucial standard in Computer Supported Collaborative Design, because many decision-makers participating in the design process have different expertise and goals. Our approach is to set up a mo..... } } @inproceedings{ieeebib28, title={ Unified particle swarm optimization for tackling operations research problems}, author = {K.E. Parsopoulos and M.N. Vrahatis}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={53 - 59}, abstract={We investigate the performance of the recently proposed unified particle swarm optimization algorithm on two categories of operations research problems, namely minimax and integer programming problems. Different variants of the algorithm are employed..... } } @inproceedings{ieeebib280, title={ Blind Detection of Multi-user Signals in Fading Channels via Discrete Particle Swarm Optimization}, author = {Zhiyong Zhang and Guoxia Qiu}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={1697 - 1701 }, abstract={Based on the feature that transmission signals belong to a limited alphabet in mobile communications, this paper formulates the blind detection problem of multi-user signals in fading channels into a quadratic programming with binary constraints. Thi..... } } @inproceedings{ieeebib281, title={ Application of An Improved Particle Swarm Optimization Algorithm for Neural Network Training*}, author = {Fuqing Zhao and Zongyi Ren and Dongmei Yu and Yahong Yang}, booktitle={International Conference on Neural Networks and Brain, 2005. ICNN\&B '05}, notes={Volume 3, 13-15 Oct. 2005}, year={2005}, pages={1693 - 1698 }, abstract={Particle Swarm Optimization (PSO) is an evolutionary computation technique developed by Kennedy and Eberhart in 1995 and has been applied successfully to various optimization problems. The PSO idea is inspired by natural concepts such as fish schooli..... } } @inproceedings{ieeebib282, title={ Particle Swarm Optimization with Local Search}, author = {Junying Chen and Zheng Qin and Yu Liu and Jiang Lu}, booktitle={International Conference on Neural Networks and Brain, 2005. ICNN\&B '05}, notes={Volume 1, 13-15 Oct. 2005}, year={2005}, pages={481 - 484 }, abstract={In this paper, we propose a hybrid algorithm of particle swarm optimization and local search (PSO-LS). In PSO-LS, each particle has a chance of self-improvement by applying local search algorithm before it communicates information with other particle..... } } @inproceedings{ieeebib283, title={ A Modified Particle Swarm Optimization Algorithm}, author = {Wen Shuhua and Zhang Xueliang and Li Hainan and Liu Shuyang and Wang Jiaying}, booktitle={International Conference on Neural Networks and Brain, 2005. ICNN\&B '05}, notes={Volume 1, 13-15 Oct. 2005}, year={2005}, pages={318 - 321 }, abstract={A modified particle swarm optimization (MPSO) algorithm is presented based on the variance of the population's fitness. During computing, the inertia weight of MPSO is determined adaptively and randomly according to the variance of the population's f..... } } @inproceedings{ieeebib284, title={ Wavelets Neural Network Based on Particle Swarm Optimization Algorithm for Fault Diagnosis}, author = {Changcheng Xiang and Xiyue Huang and Darong Huang and Jia Hu}, booktitle={First International Conference on Innovative Computing, Information and Control, 2006. ICICIC '06}, notes={Volume 3, 30-01 Aug. 2006}, year={2006}, pages={320 - 323 }, abstract={A systematic method for fault diagnosis of steam-turbine generator sets based on the combination of wavelet neural networks and particle swarm optimization is presented. Using the model of wavelet neural networks, we can not only extract the features..... } } @inproceedings{ieeebib285, title={ Optimised landmark model matching for face recognition}, author = {R. Senaratne and S. Halgamuge}, booktitle={7th International Conference on Automatic Face and Gesture Recognition, 2006. FGR 2006}, notes={10-12 April 2006}, year={2006}, pages={6 pp. }, abstract={A new method for face recognition, landmark model matching, is proposed in this paper. It is based on the concepts of elastic bunch graph matching and active shape model, and optimised with particle swarm optimisation. It is a fully automatic algorit..... } } @inproceedings{ieeebib286, title={ A particle swarm optimization approach for automatic diagnosis of PMSM stator fault}, author = {Li Liu and D.A. Cartes}, booktitle={American Control Conference, 2006}, year={2006}, notes={14-16 June 2006}, pages={6 pp. }, abstract={Permanent magnet synchronous motors (PMSM) are frequently used to high performance applications. Accurate diagnosis of small faults can significantly improve system availability and reliability. This paper proposes a new scheme for the automatic diag..... } } @inproceedings{ieeebib287, title={ Modified particle swarm optimization algorithm for steelmaking charge plan with unknown charge number}, author = {Yuncan Xue and Jun Feng and Fei Liu}, booktitle={American Control Conference, 2006}, year={2006}, notes={14-16 June 2006}, pages={5 pp. }, abstract={An optimum furnace charge plan model with unknown charge number for steelmaking continuous casting planning and scheduling is presented. Based on the analysis of the difficult to solve the problem, a pseudo travel salesman problem model is presented ..... } } @inproceedings{ieeebib288, title={ Hammerstein and Wiener nonlinear models identification using a multimodal particle swarm optimizer}, author = {A. Naitali and F. Giri}, booktitle={American Control Conference, 2006}, year={2006}, notes={14-16 June 2006}, pages={6 pp. }, abstract={A new solution to nonlinear systems identification based on Hammerstein and Wiener models, is developed using tools from evolutionary algorithms. A particle swarm optimizer including a dynamic niching procedure is resorted to find, on one hand, the p..... } } @inproceedings{ieeebib289, title={ Data Clustering with Particle Swarms}, author = {S.C.M. Cohen and L.N. de Castro}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1792 - 1798 }, abstract={This paper presents a new proposal for data clus-tering based on the particle swarm optimization (PSO) algorithm. The human tendency of adapting its behavior due to the influence of the environment minimizing the differences in opinions and ideas thr..... } } @inproceedings{ieeebib29, title={ Particle swarm optimization with mutation}, author = {A. Stacey and M. Jancic and I. Grundy}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 2, 8-12 Dec. 2003}, year={2003}, pages={1425 - 1430 Vol.2 }, abstract={The particle swarm optimization algorithms converges rapidly during the initial stages of a search, but often slows considerably and can get trapped in local optima. This paper examines the use of mutation to both speed up convergence and escape loca..... } } @inproceedings{ieeebib290, title={ A Particle Swarm Algorithm for Complex Quantised Problem Spaces}, author = {T. Hendtlass}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1015 - 1019 }, abstract={The particle swarm algorithm has shown ability to optimize in continuous problem spaces, although it can struggle in problem spaces containing multiple optima. A variant, called Waves of Swarm particles (WoSP), has been shown to be able to handle pro..... } } @inproceedings{ieeebib291, title={ An Improved Particle Swarm Optimization Algorithm for Vehicle Routing Problem with Time Windows}, author = {Qing Zhu and Limin Qian and Yingchun Li and Shanjun Zhu}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1386 - 1390 }, abstract={Vehicle Routing Problem with Time Windows (VRPTW) is of crucial importance in todays industries, accounting for a significant portion of many distribution and transportation systems. In this paper, we present a computational-efficient VRPTW al..... } } @inproceedings{ieeebib292, title={ A Genetic Binary Particle Swarm Optimization Model}, author = {J. Sadri and C.Y. Suen}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={656 - 663 }, abstract={In this paper, a Genetic Binary Particle Swarm Optimization (GBPSO) model is proposed, and its performance is compared with the regular binary Particle Swarm Optimizer (PSO), introduced by Kennedy and Eberhart. In the original model, the size of the ..... } } @inproceedings{ieeebib293, title={ Self-Organizing Swarm (SOSwarm): A Particle Swarm Algorithm for Unsupervised Learning}, author = {M. O'Neill and A. Brabazon}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={634 - 639 }, abstract={We present a novel self-organizing Particle Swarm algorithm, SOSwarm, that adopts unsupervised learning. Input vectors are projected onto a lower dimensional map space producing a visual representation of the input data in a manner similar to the Sel..... } } @inproceedings{ieeebib294, title={ Particle Swarm Optimization in Dynamic Pricing}, author = {P.B. Mullen and C.K. Monson and K.D. Seppi and S.C. Warnick}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1232 - 1239 }, abstract={Dynamic pricing is a real-time machine learning problem with scarce prior data and a concrete learning cost. While the Kalman Filter can be employed to track hidden demand parameters and extensions to it can facilitate exploration for faster learning..... } } @inproceedings{ieeebib295, title={ Application of particle swarm optimization algorithm to multiuser detection in CDMA}, author = {H.H. El-Mora and A.U. Sheikh and A., Sr. Zerguine}, booktitle={IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications, 2005. PIMRC 2005}, notes={Volume 4, 11-14 Sept. 2005}, year={2005}, pages={2522 - 2526 Vol. 4 }, abstract={Multiple access interference and near-far effect cause performance limitation in the conventional single-user detector used in direct sequence/code division multiple access (DS-CDMA)-systems. In this paper, we present a novel multiuser detector (MUD)..... } } @inproceedings{ieeebib296, title={ Stochastic collision detection between deformable models using particle swarm optimization algorithm}, author = {Wang Tianzhu and Li Wenhui and Wang Yi and Ge Zihou and Han Dongfeng}, booktitle={Multi-Media Modelling Conference Proceedings, 2006 12th International}, notes={4-6 Jan. 2006}, year={2006}, pages={4 pp. }, abstract={We present an efficient algorithm for detecting collisions and self-collisions between highly deformable mass models, which is a combination of newly developed stochastic method and particle swarm optimization (PSO) algorithm. In stochastic collision..... } } @inproceedings{ieeebib297, title={ A hybrid of /spl epsiv/-constraint and particle swarm optimization for designing of PID controllers}, author = {Ying-Tung Hsiao and Cheng-Long Chuang and Joe-Air Jiang}, booktitle={2005 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 4, 10-12 Oct. 2005}, year={2005}, pages={3063 - 3070 Vol. 4}, abstract={In this paper, an optimum approach to design PID controllers has been proposed. PID control schema based on classical control theory has been widely used in industrial control processes. Since most of the control systems have nonlinear properties, it..... } } @inproceedings{ieeebib298, title={ Quantum-behaved particle swarm optimization with mutation operator}, author = {Jing Liu and Wenbo Xu and Jun Sun}, booktitle={2005. ICTAI 05. 17th IEEE International Conference on Tools with Artificial Intelligence}, notes={14-16 Nov. 2005}, year={2005}, pages={4 pp.}, abstract={The mutation mechanism is introduced into quantum-behaved particle swarm optimization to increase its global search ability and escape from local minima. Based on the characteristic of QPSO algorithm, the variable of gbest and mbest is mutated with C..... } } @inproceedings{ieeebib299, title={ Nonlinear mapping using particle swarm optimisation}, author = {A.I. Edwards and A.P. Engelbrecht and N. Franken}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 1, 2-5 Sept. 2005}, pages={306 - 313 Vol.1 }, abstract={Large datasets consisting of high-dimensional vectors commonly describe complex objects. Having these vectors exist in a smaller dimension where the topological characteristics of the original space are preserved, allows clusters or patterns inherent..... } } @article{ieeebibJ3, title={ A novel approach for unit commitment problem via an effective hybrid particle swarm optimization}, author = {T.O. Ting and M.V.C. Rao and C.K. Loo}, journal={IEEE Transactions on Power Systems}, volume= 21, issue= 1, date={ Feb. 2006}, pages={411 - 418 }, year={2006}, abstract={This paper presents a new approach via hybrid particle swarm optimization (HPSO) scheme to solve the unit commitment (UC) problem. HPSO proposed in this paper is a blend of binary particle swarm optimization (BPSO) and real coded particle swarm optim.....} } @inproceedings{ieeebib30, title={ Particle swarm optimization-based approach for generator maintenance scheduling}, author = {Chin Aik Koay and D. Srinivasan}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={167 - 173}, abstract={This paper introduces a particle swarm optimization-based method for solving a multi-objective generator maintenance scheduling problem with many constraints. It is shown that the particle swarm optimization-based approach is effective in obtaining f..... } } @inproceedings{ieeebib300, title={ Flexible protein-ligand docking using particle swarm optimization}, author = {Bo-Fu Liu and Hung-Ming Chen and Hui-Ling Huang and Shiow-Fen Hwang and Shinn-Ying Ho}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 1, 2-5 Sept. 2005}, pages={251 - 258 Vol.1 }, abstract={Many protein-ligand docking problems attempt to predict the bound conformations of two interacting molecules. Consequently, the docking problem requires a powerful search technique to explore the translations, orientations, and each torsion until an ..... } } @inproceedings{ieeebib301, title={ Combining particle swarm optimisation with angle modulation to solve binary problems}, author = {G. Pampara and N. Franken and A.P. Engelbrecht}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 1, 2-5 Sept. 2005}, pages={89 - 96 Vol.1 }, abstract={The optimisation process of a particular problem generally has many influencing factors including the parameter choices, problem constraints as well as the complexity of the optimisation algorithm and optimisation problem among others. The dimensiona..... } } @inproceedings{ieeebib302, title={ WoSP: a multi-optima particle swarm algorithm}, author = {T. Hendtlass}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 1, 2-5 Sept. 2005}, pages={727 - 734 Vol.1 }, abstract={When investigating multi-optima problems, a particle swarm algorithm should not converge on single optima but ideally should explore many optima by continual searching. The common practice of only evaluating each particle's performance at discrete in..... } } @inproceedings{ieeebib303, title={ Dynamic multi-swarm particle swarm optimizer with local search}, author = {J.J. Liang and P.N. Suganthan}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 1, 2-5 Sept. 2005}, pages={522 - 528 Vol.1 }, abstract={In this paper, the performance of a modified dynamic multi-swarm particle swarm optimizer (DMS-PSO) on the set of benchmark functions provided by CEC2005 is reported. Different from the existing multi-swarm PSOs and local versions of PSO, the swarms ..... } } @inproceedings{ieeebib304, title={ Feature Subset Selection for Face Detection Using Genetic Algorithms and Particle Swarm Optimization}, author = {M.A. Shoorehdeli and M. Teshnehlab and H.A. Moghaddam}, booktitle={2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on Networking, Sensing and Control}, notes={23-25 April 2006}, year={2006}, pages={686 - 690}, abstract={This paper has introduced a new method for feature subset selection to which less attention has been given. The most of the past works have emphasized feature extraction, classification and using classical methods for these works. The main goal in fe..... } } @inproceedings{ieeebib305, title={ A new particle swarm optimizer algorithm and application}, author = {Bo Wang and Yunlong Dong and CanLin Wang and QinLin Qu}, booktitle={1st International Symposium on Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006}, notes={19-21 Jan. 2006}, year={2006}, pages={4 pp. }, abstract={Particle swarm optimizer (PSO) is an intelligent algorithm which simulates the hunting activity of the group of birds. It's very clear, easy-defined, simple-operation and realizable. It can be used in radar-network to solve the program of radar syste..... } } @inproceedings{ieeebib306, title={ An analysis of roulette selection in early particle swarm optimizing}, author = {Zhaofang Yang and Fang Wang}, booktitle={1st International Symposium on Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006}, notes={19-21 Jan. 2006}, year={2006}, pages={4 pp. }, abstract={In this paper, we present a novel particle swarm optimizer combined with the roulette selection operator. The modified algorithm provides a mechanism to restrain super particles in early stage and can effectively avoid the premature problem. It is em..... } } @inproceedings{ieeebib307, title={ Optimized sink node path using particle swarm optimization}, author = {C. Mendis and S.M. Guru and S. Halgamuge and S. Fernando}, booktitle={20th International Conference on Advanced Information Networking and Applications, 2006. AINA 2006}, notes={Volume 2, 18-20 April 2006}, year={2006}, pages={5 pp. }, abstract={A wireless sensor network (WSN) is comprised of large number of sensors distributed in a monitoring field and a sink node to gather process and control data. The performance of the network depends on the behavior of the sink node and its location. An..... } } @inproceedings{ieeebib308, title={ Performance optimization of elliptical flexure hinge using a modified particle swarm algorithm}, author = {Guimin Chen and Jianyuan Jia and Qi Han and Yingkun Wang}, booktitle={2005. ICIT 2005. IEEE International Conference on Industrial Technology}, notes={14-17 Dec. 2005}, year={2005}, pages={1180 - 1185}, abstract={For its excellent mechanical properties, elliptical flexure hinges have been widely used in compliant mechanisms. Based on the theory of Euler-Bernoulli beam, the compliance, stress and accuracy models of elliptical hinge were established. To design ..... } } @inproceedings{ieeebib309, title={ Particle Swarm Algorithm for Minimal Attribute Reduction of Decision Data Tables}, author = {Jianhua Dai and Weidong Chen and Hongying Gu and Yunhe Pan}, booktitle={First International Multi-Symposiums on Computer and Computational Sciences, 2006. IMSCCS '06}, notes={Volume 2, 20-24 April 2006}, year={2006}, pages={572 - 575 }, abstract={Attribute reduction is an important issue when dealing with huge amounts of data. It has been proved that computing the minimal reduct of a decision data table is NP-complete. Particle swarm algorithm is a new population based stochastic optimization..... } } @article{ieeebibJ31, title={ A Sub-boundary Approach for Enhanced Particle Swarm Optimization and Its Application to the Design of Artificial Magnetic Conductors}, author={Simone Genovesi and Agostino Monorchio and Raj Mittra and Giuliano Manara}, journal={IEEE Transactions on Antennas and Propagation}, volume= 55, issue= 3, date={}, part1={ March 2007 Page(s):766 - 770 }, year={2007}, abstract={The particle swarm algorithm is a newly introduced method for electromagnetic optimization problems that is based on the observation of swarm intelligence and particle behavior. This paper proposes a novel strategy for the initialization of the agent..... } } @inproceedings{ieeebib310, title={ Underwater Image Segmentation with Maximum Entropy based on Particle Swarm Optimization (PSO)}, author = {Rubo Zhang and Jing Liu}, booktitle={First International Multi-Symposiums on Computer and Computational Sciences, 2006. IMSCCS '06}, notes={Volume 2, 20-24 April 2006}, year={2006}, pages={360 - 636 }, abstract={The contrast of the underwater images is often extraordinarily low due to the ray, assimilating of water, illuminating condition and so on. It is not good for the pretreatment like edge detection and image segmentation. The theory of entropy has been..... } } @inproceedings{ieeebib311, title={ Evolutionary computation based optimization in fuzzy automatic generation control}, author = {R. Roy and S.P. Ghoshal}, booktitle={Power India Conference, 2006 IEEE}, notes={10-12 April 2006}, year={2006}, pages={7 pp. }, abstract={This paper presents a comparative optimization performance and transient performance studies among three evolutionary computational techniques as genetic algorithm (GA), hybrid particle swarm with constriction factor approach (HPSOCFA) and hybrid Tag..... } } @inproceedings{ieeebib312, title={ Modified particle swarm optimization algorithm for steelmaking charge plan based on the pseudo TSP model}, author = {Wei Jian and Yuncan Xue}, booktitle={Industrial Electronics Society, 2005. IECON 2005. 32nd Annual Conference of IEEE}, notes={6-10 Nov. 2005}, year={2005}, pages={5 pp. }, abstract={An optimum furnace charge plan model for steelmaking continuous casting planning and scheduling is presented. Based on the analysis of the difficult to solve the problem, a pseudo travel salesman problem model is presented to describe the plan and sc..... } } @inproceedings{ieeebib313, title={ Adaptive inverse control based on particle swarm optimization algorithm}, author = {YuShen Wang and KeJun Wang and JiaSheng Qu and YuRong Yang}, booktitle={2005 IEEE International Conference Mechatronics and Automation}, notes={Volume 4, 29 July-1 Aug. 2005}, year={2005}, pages={2169 - 2172 Vol. 4}, abstract={Two off-line neural networks were trained by applying particle swarm optimization algorithm to create object model and object inverse model of model reference adaptive inverse control system. The method and procedure in training the network of contro..... } } @inproceedings{ieeebib314, title={ Simulation-based optimization for repairable systems using particle swarm algorithm}, author = {T.M. Alkhamis and M.A. Ahmed}, booktitle={Winter Simulation Conference, 2005 Proceedings of the}, notes={4-7 Dec. 2005}, year={2005}, pages={5 pp. }, abstract={We describe an approach based on particle swarm optimization (PSO) for determining the optimal allocation of spares as well as repair resources while satisfying a desired availability constraint. The proposed method expands the original PSO algorithm..... } } @inproceedings{ieeebib315, title={ Reactive power control based on particle swarm multi-objective optimization}, author = {J.G. Vlachogiannis and K.Y. Lee}, booktitle={Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, 2005}, notes={6-10 Nov. 2005}, year={2005}, pages={5 pp. }, abstract={In this study the state-of-the-art extended particle swarm optimization (PSO) methods for solving multi-objective problems are represented. We emphasize in those, which use the co-evolution technique of the parallel vector evaluated PSO (VEPSO), anal..... } } @inproceedings{ieeebib316, title={ Particle swarm optimization for economic dispatch of units with non-smooth input-output characteristic functions}, author = {L.L. Lai and T.Y. Nieh and D. Vujatovic and Y.N. Ma and Y.P. Lu and Y.W. Wang and H. Braun}, booktitle={Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, 2005}, notes={6-10 Nov. 2005}, year={2005}, pages={5 pp. }, abstract={This paper proposes an application of particle swarm optimization (PSO) to solve economic dispatch (ED) of units with non-smooth input-output characteristic functions. The IEEE 30-bus system with 6 generating units has been used as the simulation sys..... } } @inproceedings{ieeebib317, title={ Constrained optimal power flow by mixed-integer particle swarm optimization}, author = {Zwe-lee Gaing}, booktitle={Power Engineering Society General Meeting, 2005. IEEE}, notes={12-16 June 2005}, year={2005}, pages={243 - 250 Vol. 1 }, abstract={This paper presents an efficient mixed-integer particle swarm optimization (MIPSO) for solving the constrained optimal power flow (OPF) with a mixture of continuous and discrete control variables and discontinuous fuel cost functions. In the MIPSO-ba..... } } @inproceedings{ieeebib318, title={ A perturbation particle swarm optimization for the synthesis of the radiation pattern of antenna array}, author = {Zhihao Yuan and Ronghong Jin and Junping Geng and Yu Fan and Jia Lao and Jiaqiang Li and Xianyi Rui and Zhijiang Fang and Jing Sun}, booktitle={Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings}, notes={Volume 3, 4-7 Dec. 2005}, year={2005}, pages={4 pp. }, abstract={In this paper, a modified particle swarm optimization algorithm is proposed, in which special techniques such as global best perturbation and inertia weight jump threshold are adopted. The convergence speed and accuracy are improved. Using it, the pr..... } } @inproceedings{ieeebib319, title={ Floorplanning based on particle swarm optimization}, author = {Tsung-Ying Sun and Sheng-Ta Hsieh and Hsiang-Min Wang and Cheng-Wei Lin}, booktitle={IEEE Computer Society Annual Symposium on Emerging VLSI Technologies and Architectures, 2006}, notes={Volume 00, 2-3 March 2006}, year={2006}, pages={5 pp. }, abstract={This paper presents a floorplanning method based on particle swarm optimization (PSO). We adopted the B*-tree floorplan structure to generate an initial stage with overlap free for placement and utilized PSO to find out the potential optimal placemen..... } } @inproceedings{ieeebib32, title={ Particle Swarm Optimization for the Design of Frequency Selective Surfaces}, author = {S. Genovesi and R. Mittra and A. Monorchio and G. Manara}, booktitle={Antennas and Wireless Propagation Letters}, notes={Volume 5, Issue 1, Dec. 2006}, year={2006}, pages={277 - 279 }, abstract={The particle swarm optimization (PSO) is a stochastic strategy that has recently found application to electromagnetic optimization problems. It is based on the behavior of insect swarms and exploits the solution space by taking into account the exper..... } } @inproceedings{ieeebib320, title={ An adaptive diversity strategy for particle swarm optimization}, author = {Fang Wang and Naiqin Feng and Yuhui Qiu}, booktitle={2005. IEEE NLP-KE '05. Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering}, notes={30 Oct.-1 Nov. 2005}, year={2005}, pages={760 - 764}, abstract={In this paper, we present a diversity strategy for particle swarm optimizer. The modified algorithm re-initializes part of particles with poorer fitness during the searching process. It is empirically tested and compared with other published methods ..... } } @inproceedings{ieeebib321, title={ Power system stability enhancement using backstepping controller tuned by particle swarm optimization technique}, author = {A. Karimi and A. Al-Hinai and K. Schoder and A. Feliachi}, booktitle={Power Engineering Society General Meeting, 2005. IEEE}, notes={12-16 June 2005}, year={2005}, pages={1388 - 1395 Vol. 2 }, abstract={A method for designing controls through the excitation system and particle swarm optimization technique to search for the optimal setting of the controller gains to improve transient stability and damping is presented. Simulation of multi-machine pow..... } } @inproceedings{ieeebib322, title={ Significance of neighborhood topologies for the reconstruction of microwave images using particle swarm optimization}, author = {T. Huang and A.S. Mohan}, booktitle={Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings}, notes={Volume 1, 4-7 Dec. 2005}, year={2005}, pages={4 pp. }, abstract={Recently, the use of the particle swarm optimization (PSO) technique for the reconstruction of microwave images has been reported. However, the standard version of the PSO technique may suffer from the problem of premature convergence, as the particl..... } } @inproceedings{ieeebib323, title={ Adaptive array digital beamforming using complex-coded particle swarm optimization-genetic algorithm}, author = {Beng-Kiong Yeo and Yilong Lu}, booktitle={Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings}, notes={Volume 2, 4-7 Dec. 2005}, year={2005}, pages={3 pp. }, abstract={In this paper, a flexible approach using hybrid particle swarm optimization-genetic algorithm (PSO-GA) is proposed for fast adaptive wide steering and array failure correction in digital beamforming of arbitrary arrays. Examples of wide steering an..... } } @inproceedings{ieeebib324, title={ FDTD time series extrapolation by the least squares support vector machine method with the particle swarm optimization technique}, author = {Y. Yang and R.S. Chen and Z.B. Ye and Z. Liu}, booktitle={Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings}, notes={Volume 4, 4-7 Dec. 2005}, year={2005}, pages={3 pp. }, abstract={A new combination of particle swarm optimization (PSO) and least-squares support vector machines (LS-SVM) technique for FDTD time series forecasting is presented. In this paper, the PSO is extended to optimize the hyperparameter used in the LS-SVM al..... } } @inproceedings{ieeebib325, title={ A modified particle swarm optimizer with roulette selection operator}, author = {Fang Wang and Yuhui Qiu}, booktitle={2005. IEEE NLP-KE '05. Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering}, notes={30 Oct.-1 Nov. 2005}, year={2005}, pages={765 - 768}, abstract={In this paper, a novel particle swarm optimizer combined with the roulette selection operator is proposed, which provides a mechanism to restrain the predominating of super particles in early stage and can effectively avoid the premature problem. We ..... } } @inproceedings{ieeebib326, title={ Performance tuning of evolutionary algorithms using particle sub swarms}, author = {C. Grosan and A. Abraham and M. Nicoara}, booktitle={Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2005. SYNASC 2005}, notes={25-29 Sept. 2005}, year={2005}, pages={8 pp. }, abstract={Particle swarm optimization (PSO) technique proved its ability to deal with very complicated optimization and search problems. This paper proposes a new particle swarm variant which deals with sub-populations. This algorithm is applied for solving th..... } } @inproceedings{ieeebib327, title={ Investigation of particle swarm optimization for dynamic reconfiguration of field-programmable analog circuits}, author = {P. Tawdross and A. Konig}, booktitle={Fifth International Conference on Hybrid Intelligent Systems, 2005}, notes={6-9 Nov. 2005}, year={2005}, pages={6 pp. }, abstract={The sensor electronics and mixed signal processing circuits are sensitive to aging, temperature distribution inside the chip, manufacturing tolerance, or additional factors of the external environment. These influences can't be effectively considered..... } } @inproceedings{ieeebib328, title={ Particle swarm optimization (PSO) applied to fuzzy modeling in a thermal-vacuum system}, author = {R. Marinke and E. Araujo and Ld.S. Coelho and I. Matiko}, booktitle={Fifth International Conference on Hybrid Intelligent Systems, 2005}, notes={6-9 Nov. 2005}, year={2005}, pages={6 pp. }, abstract={A nonlinear identification approach based on particle swarm optimization (PSO) and Takagi-Sugeno (T-S) fuzzy model for describing dynamical behavior of a thermal-vacuum system is proposed in this paper. Identification of nonlinear systems is an impor..... } } @inproceedings{ieeebib329, title={ Radial basis neural network learning based on particle swarm optimization to multistep prediction of chaotic Lorenz's system}, author = {F.A. Guerra and L.D.S. Coelho}, booktitle={Fifth International Conference on Hybrid Intelligent Systems, 2005}, notes={6-9 Nov. 2005}, year={2005}, pages={3 pp. }, abstract={This paper presents a hybrid training approach to radial basis function neural networks (RBF-NN). It uses clustering methods to tune the centers of the Gaussian functions used in the hidden layer of a RBF-NN. It also uses particle swarm optimization ..... } } @article{ieeebibJ33, title={ Neighborhood topologies in fully informed and best-of-neighborhood particle swarms}, author={J. Kennedy and R. Mendes}, journal={IEEE Transactions on Systems, Man and Cybernetics, Part C}, volume= 36, issue= 4, date={ July 2006}, pages={515 - 519 }, year={2006}, abstract={In this study, we vary the way an individual in the particle swarm interacts with its neighbors. The performance of an individual depends on population topology as well as algorithm version. It appears that a fully informed particle swarm is more sus..... } } @inproceedings{ieeebib330, title={ Fuzzy adaptive turbulent particle swarm optimization}, author = {Hongbo Liu and A. Abraham}, booktitle={Fifth International Conference on Hybrid Intelligent Systems, 2005}, notes={6-9 Nov. 2005}, year={2005}, pages={6 pp. }, abstract={In this paper, we introduce turbulence in the particle swarm optimization (TPSO) and illustrate how this approach could be used for function optimization problems involving high dimensions. The proposed algorithm uses a minimum velocity threshold to ..... } } @inproceedings{ieeebib331, title={ A ridgelet kernel approach for regression using particle swarm optimization algorithm}, author = {Shuyuan Yang and Min Wang and Licheng Jiao}, booktitle={2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05. Proceedings}, notes={Volume 5, 31 July-4 Aug. 2005}, year={2005}, pages={2837 - 2842 vol. 5 }, abstract={In this paper, a ridgelet kernel approach is proposed for approximation of multivariate functions, especially those with certain kinds of spatial inhomogeneities. It is based on ridgelet theory, kernel and regularization technology from which we can ..... } } @inproceedings{ieeebib332, title={ Optimizing class-related thresholds with particle swarm optimization}, author = {L.S. Oliveira and A.S., Jr. Britto and R. Sabourin}, booktitle={2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05. Proceedings}, notes={Volume 3, 31 July-4 Aug. 2005}, year={2005}, pages={1511 - 1516 vol. 3 }, abstract={In this paper we address the issue of class-related reject thresholds for classification systems. It has been demonstrated in the literature that class related reject thresholds provide an error-reject tradeoff better than a single global threshold. ..... } } @inproceedings{ieeebib333, title={ Improved particle swarm optimization algorithm for optimum charge plan for steelmaking-continuous casting production scheduling}, author = {Yuncan Xue and Qiwen Yang and Wei Jian}, booktitle={2005. INDIN '05. 2005 3rd IEEE International Conference on Industrial Informatics}, notes={10-12 Aug. 2005}, year={2005}, pages={558 - 561}, abstract={An optimum furnace charge plan model for steelmaking continuous casting planning and scheduling is presented. An improved particle swarm optimization with disturbances is presented to solve the optimum charge plan problem. In order to find the premat..... } } @inproceedings{ieeebib334, title={ Nonlinear mappings based on particle swarm optimization}, author = {C.J. Figueroa and P.A. Estevez and R.E. Hernandez}, booktitle={2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05. Proceedings}, notes={Volume 3, 31 July-4 Aug. 2005}, year={2005}, pages={1487 - 1492 vol. 3 }, abstract={Nonlinear mapping methods that minimize the Sammon stress based on particle swarm optimization (PSO) are proposed. The task considered is the mapping of the codebook vectors generated by the neural gas (NG) network onto a two-dimensional space. Three..... } } @inproceedings{ieeebib335, title={ Stochastic Multi Objective Short Term Hydrothermal Scheduling Using Particle Swarm Optimization}, author = {S.P. Umayal and N. Kamaraj}, booktitle={INDICON, 2005 Annual IEEE}, notes={11-13 Dec. 2005}, year={2005}, pages={497 - 501 }, abstract={In the multi objective framework particle swarm optimization technique is used to find the generation schedule of a short-range fixed head hydrothermal problem, through the improvement of the selection manner for global and individual extreme. The mu..... } } @inproceedings{ieeebib336, title={ A Framework for Identification of Fuzzy Models through Particle Swarm Optimization Algorithm}, author = {A. Khosla and S. Kumar and K.K. Aggarwal}, booktitle={INDICON, 2005 Annual IEEE}, notes={11-13 Dec. 2005}, year={2005}, pages={388 - 391 }, abstract={This paper presents a framework for the identification of fuzzy models from the available input-output data through Particle Swarm Optimization (PSO) algorithm. Like other evolutionary algorithms, PSO is a population-based stochastic algorithm and is..... } } @inproceedings{ieeebib337, title={ Multiuser detection using the particle swarm optimization algorithm}, author = {Cheng Liu and Yang Xiao}, booktitle={IEEE International Symposium on Communications and Information Technology, 2005. ISCIT 2005}, notes={Volume 1, 12-14 Oct. 2005}, year={2005}, pages={362 - 365 }, abstract={Genetic algorithm (GA) has proven to be a useful method of optimization for multidimensional engineering problems. A new method named particle swarm optimization (PSO) has been proposed by Kennedy and Eberhart and it is similar in some ways to GA or ..... } } @inproceedings{ieeebib338, title={ Interactive particle swarm optimization}, author = {J. Madar and J. Abonyi and F. Szeifert}, booktitle={5th International Conference on Intelligent Systems Design and Applications, 2005. ISDA '05. Proceedings}, notes={8-10 Sept. 2005}, year={2005}, pages={314 - 319 }, abstract={It is often desirable to simultaneously handle several objectives and constraints in practical optimization problems. In some cases, these objectives and constraints are non-commensurable and they are not explicitly/mathematically available. For this..... } } @inproceedings{ieeebib339, title={ Empirical study of hybrid particle swarm optimizers with the simplex method operator}, author = {Fang Wang and Yuhui Qiu}, booktitle={5th International Conference on Intelligent Systems Design and Applications, 2005. ISDA '05. Proceedings}, notes={8-10 Sept. 2005}, year={2005}, pages={308 - 313 }, abstract={A novel hybrid simplex method and particle swarm optimization (HSMPSO) algorithm is presented in this article. Computational experiments on variety of benchmark functions indicate this SM-PSO hybrid is a promising way for locating global optima of co..... } } @article{ieeebibJ34, title={ Stability analysis of the particle dynamics in particle swarm optimizer}, author={V. Kadirkamanathan and K. Selvarajah and P.J. Fleming}, journal={IEEE Transactions on Evolutionary Computation}, volume= 10, issue= 3, date={ June 2006}, pages={245 - 255 }, year={2006}, abstract={Previous stability analysis of the particle swarm optimizer was restricted to the assumption that all parameters are nonrandom, in effect a deterministic particle swarm optimizer. We analyze the stability of the particle dynamics without this restric..... } } @inproceedings{ieeebib340, title={ Adapting particle swarm optimization to stock markets}, author = {J. Nenortaite and R. Simutis}, booktitle={5th International Conference on Intelligent Systems Design and Applications, 2005. ISDA '05. Proceedings}, notes={8-10 Sept. 2005}, year={2005}, pages={520 - 525 }, abstract={The paper is focused on the development of intelligent decision-making model which is based on the application of artificial neural networks (ANN) and swarm intelligence algorithm. The proposed model generates one-step forward investment decisions. T..... } } @inproceedings{ieeebib341, title={ Parallelizing particle swarm optimization}, author = {Bo Li and Koichi Wada}, booktitle={2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005. PACRIM}, notes={24-26 Aug. 2005}, year={2005}, pages={288 - 291 }, abstract={This paper focuses on a parallel version of particle swarm optimization (PSO) algorithm which can significantly reduces execution time for solving complex large-scale optimization problems. This paper gives an overview of PSO algorithm, and then prop..... } } @inproceedings{ieeebib342, title={ A particle swarm optimiser with passive congregation approach to thermal modelling for power transformers}, author = {W.H. Tang and S. He and E. Prempain and Q.H. Wu and J. Fitch}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 3, 2-5 Sept. 2005}, pages={2745 - 2751 Vol. 3 }, abstract={This paper employs an intelligent learning technique based on a particle swarm optimiser with passive congregation (PSOPC) algorithm to identify the thermal parameters of a simplified thermoelectric analogous thermal model (STEATM) for transformers, ..... } } @inproceedings{ieeebib343, title={ Modeling and analysis of indirect communication in particle swarm optimization}, author = {S. Helwig and C. Haubelt and J. Teich}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 2, 2-5 Sept. 2005}, pages={1246 - 1253 Vol. 2 }, abstract={Particle swarm optimization (PSO) has successfully been applied to many optimization problems. One particularly interesting aspect of these algorithms is to study the communication behavior of the particles. Often, a neighborhood topology is defined ..... } } @inproceedings{ieeebib344, title={ Gaussian particle swarm with jumps}, author = {R.A. Krohling}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 2, 2-5 Sept. 2005}, pages={1226 - 1231 Vol. 2 }, abstract={Gaussian particle swarm optimization (GPSO) algorithm has shown promising results for solving multimodal optimization problems in low dimensional search space. But similar to evolutionary algorithms (EAs), GPSO may also get stuck in local minima when..... } } @inproceedings{ieeebib345, title={ Enhanced particle swarm optimization through external memory support}, author = {A. Acan and A. Gunay}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 2, 2-5 Sept. 2005}, pages={1875 - 1882 Vol. 2 }, abstract={A particle swarm optimization strategy using an external memory of partial position and velocity vectors for the purpose of achieving better and faster search capabilities is introduced. Partially complete position and velocity vectors stored in memo..... } } @inproceedings{ieeebib346, title={ Performance analysis of grinding process via particle swarm optimization}, author = {T.O. Ting and T.S. Lee and T. Htay}, booktitle={Sixth International Conference on Computational Intelligence and Multimedia Applications, 2005}, notes={16-18 Aug. 2005}, year={2005}, pages={92 - 97 }, abstract={Optimization is necessary for the control of any process to achieve better product quality, high productivity with low cost. The grinding of silicon carbide is not an easy task due to its low fracture toughness, making the material sensitive to crack..... } } @inproceedings{ieeebib347, title={ Fuzzy PSO: a generalization of particle swarm optimization}, author = {A.M. Abdelbar and S. Abdelshahid and D.C., II Wunsch}, booktitle={2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05. Proceedings}, notes={Volume 2, 31 July-4 Aug. 2005}, year={2005}, pages={1086 - 1091 vol. 2 }, abstract={In standard particle swarm optimization (PSO), the best particle in each neighborhood exerts its influence over other particles in the neighborhood. In this paper, we propose fuzzy PSO, a generalization which differs from standard PSO in the followin..... } } @inproceedings{ieeebib348, title={ Document clustering using particle swarm optimization}, author = {X. Cui and T.E. Potok and P. Palathingal}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={185 - 191}, abstract={Fast and high-quality document clustering algorithms play an important role in effectively navigating, summarizing, and organizing information. Recent studies have shown that partitional clustering algorithms are more suitable for clustering large da..... } } @inproceedings{ieeebib349, title={ Parameter tuning of a computed-torque controller for a 5 degree of freedom robot arm using co-evolutionary particle swarm optimization}, author = {A. Asmara and R.A. Krohling and F. Hoffmann}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={162 - 168}, abstract={This paper proposes an accelerated co-evolutionary particle swarm optimization method to solve the problem of parameter tuning of a feedforward computed-torque controller (CTC) of a 5-DOF robot arm manipulator. The approach is based on a competitive ..... } } @article{ieeebibJ35, title={ An innovative computational approach based on a particle swarm strategy for adaptive phased-arrays control}, author={M. Donelli and R. Azaro and F.G.B. De Natale and A. Massa}, journal={IEEE Transactions on Antennas and Propagation}, volume= 54, issue= 3, date={ March 2006}, pages={888 - 898 }, year={2006}, abstract={In this paper a new approach to the control of phased arrays is presented and assessed. Starting from the adaptive array theory, a particle swarm strategy is used to tune the phase coefficients of the array in order to adaptively minimize/avoid the e..... } } @inproceedings{ieeebib350, title={ A particle swarm algorithm for high dimensional, multi-optima problem spaces}, author = {T. Hendtlass}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={149 - 154}, abstract={The same mechanisms that are so efficient at finding optima may result in a conventional particle swarm optimisation (PSO) algorithm becoming trapped in a local optimum and unable to escape from this to search for further, hopefully better, optima. T..... } } @inproceedings{ieeebib351, title={ Neural networks based non-uniform scalar quantizer design with particle swarm optimization}, author = {W. Zha and G.K. Venayagamoorthy}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={143 - 148}, abstract={Quantization is a crucial link in the process of digital speech communication. Non-uniform quantizer such as the logarithm quantizers are commonly used in practice. In this paper, a companding non-uniform quantizer is designed using two neural networ..... } } @inproceedings{ieeebib352, title={ Dynamic multi-swarm particle swarm optimizer}, author = {J.J. Liang and P.N. Suganthan}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={124 - 129}, abstract={In this paper, a novel dynamic multi-swarm particle swarm optimizer (PSO) is introduced. Different from the existing multi-swarm PSOs and the local version of PSO, the swarms are dynamic and the swarms' size is small. The whole population is divided ..... } } @inproceedings{ieeebib353, title={ Fitness inheritance in multi-objective particle swarm optimization}, author = {M. Reyes-Sierra and C.A.C. Coello}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={116 - 123}, abstract={In this paper, we propose to incorporate the concept of fitness inheritance into a multi-objective particle swarm optimizer previously proposed by us, in order to reduce the number of function evaluations performed. Four well-known test functions tak..... } } @inproceedings{ieeebib354, title={ Particle swarm optimization with area of influence: increasing the effectiveness of the swarm}, author = {K.J. Binkley and M. Hagiwara}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={45 - 52}, abstract={In this paper we present a new definition of neighborhood for particle swarm optimization (PSO) methods called area of influence. Area of influence (AOI) derives from the observation that in nature the effective exchange of information between indivi..... } } @inproceedings{ieeebib355, title={ A particle swarm optimization approach for reactive power dispatch}, author = {J.J. Jimenez-Nunez and J.R. Cedeno-Maldonado}, booktitle={Power Symposium, 2005. Proceedings of the 37th Annual North American}, notes={23-25 Oct. 2005}, year={2005}, pages={198 - 205 }, abstract={This paper presents a particle swarm optimization approach for solving the reactive power dispatch problem. The reactive power dispatch problem is formulated as a nonlinear constrained optimization problem with continuous and discrete variables. The ..... } } @inproceedings{ieeebib356, title={ Shape matching using fuzzy discrete particle swarm optimization}, author = {Ji-Xiang Du and De-Shuang Huang and Jun Zhang and Xiao-Feng Wang}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={405 - 408}, abstract={In this paper an efficient shape matching approach based on fuzzy discrete particle swarm optimization (FDPSO) is proposed. Based on fuzzy theory and PSO method, we applied this optimization method to a special combinatorial optimization problem: sha..... } } @inproceedings{ieeebib357, title={ Niching ability of basic particle swarm optimization algorithms}, author = {A.P. Engelbrecht and B.S. Masiye and G. Pampard}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={397 - 400}, abstract={Niching algorithms have the ability to locate and maintain more than one solution to a multi-modal optimization problem. Recently, niching algorithms have been developed for particle swarm optimization (PSO) to locate multiple optima. This paper inve..... } } @inproceedings{ieeebib358, title={ Improving the performance of particle swarm optimization using adaptive critics designs}, author = {S. Doctor and G.K. Venayagamoorthy}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={393 - 396}, abstract={Swarm intelligence algorithms are based on natural behaviors. Particle swarm optimization (PSO) is a stochastic search and optimization tool. Changes in the PSO parameters, namely the inertia weight and the cognitive and social acceleration constants..... } } @inproceedings{ieeebib359, title={ Distributed sensor placement with sequential particle swarm optimization}, author = {P.N. Ngatchou and W.L.J. Fox and M.A. El-Sharkawi}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={385 - 388}, abstract={Sequential particle swarm optimization (S-PSO) is a modification of PSO suitable for high-dimensional optimization problems. S-PSO iteratively optimizes the objective function over randomly selected subspaces of the parameter search space instead of ..... } } @article{ieeebibJ36, title={ A hybrid particle swarm optimization for distribution state estimation}, author={S. Naka and T. Genji and T. Yura and Y. Fukuyama}, journal={IEEE Transactions on Power Systems}, volume= 18, issue= 1, date={ Feb. 2003}, pages={60 - 68 }, year={2003}, abstract={This paper proposes a hybrid particle swarm optimization (HPSO) for a practical distribution state estimation. The proposed method considers nonlinear characteristics of the practical equipment and actual limited measurements in distribution systems...... } } @inproceedings{ieeebib360, title={ DNA motif detection using particle swarm optimization and expectation-maximization}, author = {C.T. Hardin and E.C. Rouchka}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={181 - 184}, abstract={Motif discovery, the process of discovering a meaningful pattern of nucleotides or amino acids that is shared by two or more molecules, is an important part of the study of gene function. In this paper, we propose a hybrid motif discovery approach ba..... } } @inproceedings{ieeebib361, title={ Particle swarm optimization for macrocell overlap removal and placement}, author = {Sheng-Ta Hsieh and Cheng-Wei Lin and Tsung-Ying Sun}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={177 - 180}, abstract={This paper proposes a novel algorithm based on the particle swarm optimization (PSO) technique to obtain a feasible macrocell floorplanning without overlaps in VLSI circuit physical placement. The PSO was applied with an overlap detection and removal..... } } @inproceedings{ieeebib362, title={ Comparison of particle swarm optimizations for optimal operational planning of energy plants}, author = {S. Kitagawa and Y. Fukuyama}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={155 - 161}, abstract={This paper compares particle swarm optimizations (PSOs) for optimal operational planning of energy plants. In order to generate optimal operational planning for energy plants, startup/shutdown status and/or input/output values of the facilities for e..... } } @inproceedings{ieeebib363, title={ Particle swarm over scene matching}, author = {O. Sjahputera and J.M. Keller}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={108 - 115}, abstract={Advances in a scene matching approach based on objects spatial relationships are discussed. Objects spatial relationships are captured using force histograms, which are used as affine-invariant image descriptors. Object mapping across images is perfo..... } } @inproceedings{ieeebib364, title={ A proposal to use stripes to maintain diversity in a multi-objective particle swarm optimizer}, author = {M.A. Villalobos-Arias and G.T. Pulido and C.A.C. Coello}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={22 - 29}, abstract={In this paper, we propose a new mechanism to maintain diversity in multi-objective optimization problems. The proposed mechanism is based on the use of stripes that are applied on objective function space and that is independent of the search engine ..... } } @inproceedings{ieeebib365, title={ An extended particle swarm optimizer}, author = {Xu Jun-jie and Xin Zhan-hong}, booktitle={Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium, 2005. }, notes={4-8 April 2005}, year={2005}, pages={5 pp. }, abstract={An extended particle swarm optimizer (EPSO) is proposed in this paper. In this new algorithm, not only the local but also the global best positions found so far will involve in the particle's velocity updating process. EPSO is an integration of two p..... } } @inproceedings{ieeebib366, title={ Particle swarm optimization of miniaturized quadrature reflection phase structure for low-profile antenna applications}, author = {Nanbo Jin and Y. Rahmat-Samii}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 2B, 3-8 July 2005}, year={2005}, pages={255 - 258 vol. 2B }, abstract={A new terminology, quadrature reflection phase structure (QRPS), is defined. Without applying traditional methods, such as effective circuit modeling, a parallel PSO/FDTD (particle swarm optimization/finite difference time-domain) algorithm is utiliz..... } } @inproceedings{ieeebib367, title={ Miniature three-element stochastic Yagi-Uda array optimization via particle swarm intelligence}, author = {Z. Bayraktar and P.L. Werner and D.H. Werner}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 2B, 3-8 July 2005}, year={2005}, pages={263 - 266 vol. 2B }, abstract={The relatively new nature-based algorithm, particle swarm optimization, is used to design optimal miniaturized stochastic Yagi-Uda arrays. The PSO scheme utilizes a fixed-length grid mapping of continuous values. In the conventional sense, the driven..... } } @inproceedings{ieeebib368, title={ Design of planar microwave filters using a simple FDTD model and particle swarm optimization}, author = {A. Mahanfar and S. Bila and M. Aubourg and S. Verdeyme}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 2B, 3-8 July 2005}, year={2005}, pages={259 - 262 vol. 2B }, abstract={Evolutionary algorithms (EA), such as the genetic algorithm (GA), have found wide popularity because of their capability of global optimum search. As an answer to the quest for faster converging evolutionary algorithms, particle swarm optimization (P..... )} } @inproceedings{ieeebib369, title={ Comparison of non-uniform optimal quantizer designs for speech coding with adaptive critics and particle swarm}, author = {W. Zha and G.K. Venayagamoorthy}, booktitle={Industry Applications Conference, 2005. Fourtieth IAS Annual Meeting. Conference Record of the 2005}, year={2005}, notes={Volume 1, 2-6 Oct. 2005}, pages={674 - 679 Vol. 1 }, abstract={This paper presents the design of a companding non-uniform optimal scalar quantizer for speech coding. The quantizer is designed using two neural networks to perform the nonlinear transformation. These neural networks are used in the front and back e..... } } @article{ieeebibJ37, title={ The particle swarm - explosion, stability, and convergence in a multidimensional complex space}, author={M. Clerc and J. Kennedy}, journal={IEEE Transactions on Evolutionary Computation}, volume= 6, issue= 1, date={ Feb. 2002}, pages={58 - 73 }, year={2002}, abstract={The particle swarm is an algorithm for finding optimal regions of complex search spaces through the interaction of individuals in a population of particles. This paper analyzes a particle's trajectory as it moves in discrete time (the algebraic view)..... } } @inproceedings{ieeebib370, title={ Improved particle swarm optimization algorithm for optimum charge plan for steelmaking-continuous casting production scheduling}, author = {Wei Jian and Yuncan Xue and Jiao Huang}, booktitle={2004. IEEE ICIT '04. 2004 IEEE International Conference on Industrial Technology}, notes={Volume 3, 8-10 Dec. 2004}, year={2004}, pages={1173 - 1176 Vol. 3}, abstract={An optimum furnace charge plan model for steelmaking continuous casting planning and scheduling is presented. An improved particle swarm optimization is presented to solve the optimum charge plan problem. Simulations have been carried and the results..... } } @inproceedings{ieeebib371, title={ Modified Particle Swarm Algorithm for Decentralized Swarm Agents}, author = {D.H. Kim and Seiichi Shin}, booktitle={2004. ROBIO 2004. IEEE International Conference on Robotics and Biomimetics}, notes={22-26 Aug. 2004}, year={2004}, pages={746 - 751}, abstract={In this paper, an attempt has been made by in corporating some special features in the conventional particle swarm optimization (PSO) technique for decentralized swarm agents. The modified particle swarm algorithm (MPSA) for the self-organization of ..... } } @inproceedings{ieeebib372, title={ Multi-optimum programming based particle swarm optimization algorithm and its application in multi-dimensional \& multi-modal function optimization}, author = {Wang Lei and Kang Qi and Zuo Zhenyu and Wu Qidi}, booktitle={2004. Proceedings of the 2004 IEEE International Conference on Control Applications}, notes={Volume 1, 2-4 Sept. 2004}, year={2004}, pages={149 - 152 Vol.1}, abstract={In this paper, the knowledge of multi-optimum distribution state is introduced into general programming of the particle swarm movement to avoid falling into local optimums at the original stage of the computation. The algorithm is improved based on t..... } } @inproceedings{ieeebib373, title={ Particle swarm optimization for sequencing problems: a case study}, author = {L. Cagnina and S. Esquivel and R. Gallard}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={536 - 541 Vol.1 }, abstract={PSO has been successfully used in different areas (e. g. multidimensional and multiobjective optimization, neural networks training, etc.) but there are few reports on research in sequencing problems. In this paper we present a hybrid particle swarm ..... } } @inproceedings{ieeebib374, title={ PSO with sharing for multimodal function optimization}, author = {Tao Li and Chengjian Wei and Wenjang Pei}, booktitle={Proceedings of the 2003 International Conference on Neural Networks and Signal Processing, 2003}, notes={Volume 1, 14-17 Dec. 2003}, year={2003}, pages={450 - 453 Vol.1 }, abstract={The particle swarm optimizer (PSO) has exhibited good performance on unimodal problem. But on multimodal problem it tends to suffer from premature convergence. In this paper, we propose a modification of the base PSO named fitness sharing particle sw..... } } @inproceedings{ieeebib375, title={ Training support vector machines with particle swarms}, author = {U. Paquet and A.P. Engelbrecht}, booktitle={Proceedings of the International Joint Conference on Neural Networks, 2003}, notes={Volume 2, 20-24 July 2003}, year={2003}, pages={1593 - 1598 vol.2 }, abstract={Training a support vector machine requires solving a constrained quadratic programming problem. Linear particle swarm optimization is intuitive and simple to implement, and is presented as an alternative to current numeric SVM training methods. Perfo..... } } @inproceedings{ieeebib376, title={ Parasitic-aware design and optimization of a fully integrated CMOS wideband amplifier}, author = {Jinho Park and Kiyong Choi and D.J. Allstot}, booktitle={Design Automation Conference, 2003. Proceedings of the ASP-DAC 2003. Asia and South Pacific}, notes={21-24 Jan. 2003}, year={2003}, pages={904 - 907 }, abstract={A custom CAD synthesis tool based on particle swarm optimization, and results from the design of an RF CMOS distributed amplifier optimized to overcome non-idealities associated with parasitic-laden passives, are presented. The particle swarm synthes..... } } @inproceedings{ieeebib377, title={ Hybrid particle swarm optimizer with mass extinction}, author = {Xiao-Feng Xie and Wen-Jun Zhang and Zhi-Lian Yang}, booktitle={IEEE 2002 International Conference on Communications, Circuits and Systems and West Sino Expositions}, notes={Volume 2, 29 June-1 July 2002}, year={2002}, pages={1170 - 1173 vol.2 }, abstract={A hybrid particle swarm optimizer with mass extinction, which has been suggested to be an important mechanism for evolutionary progress in the biological world, is presented to enhance the capacity in reaching an optimal solution. The tested results ..... } } @inproceedings{ieeebib378, title={ Population structure and particle swarm performance}, author = {J. Kennedy and R. Mendes}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1671 - 1676 }, abstract={The effects of various population topologies on the particle swarm algorithm were systematically investigated. Random graphs were generated to specifications, and their performance on several criteria was compared. What makes a good population struct..... } } @inproceedings{ieeebib379, title={ Fuzzy adaptive particle swarm optimization}, author = {Yuhui Shi and R.C. Eberhart}, booktitle={Proceedings of the 2001 Congress on Evolutionary Computation, 2001}, notes={Volume 1, 27-30 May 2001}, year={2001}, pages={101 - 106 vol. 1 }, abstract={A fuzzy system is implemented to dynamically adapt the inertia weight of the particle swarm optimization algorithm (PSO). Three benchmark functions with asymmetric initial range settings are selected as the test functions. The same fuzzy system has b..... } } @inproceedings{ieeebib38, title={ Particle Swarm Optimization for Operational Parameters of Series Hybrid Electric Vehicle}, author = {Zhancheng Wang and Bufu Huang and Weimin Li and Yangsheng Xu}, booktitle={2006. ROBIO '06. IEEE International Conference on Robotics and Biomimetics}, notes={Dec. 2006}, year={2006}, pages={682 - 688}, abstract={Because of the inherent advantages, i. e. increased fuel economy, reduced harmful emissions and better vehicle performance, Hybrid Electric Vehicles (HEV), powered by Internal Combustion Engine (ICE) and energy storage, are being given more and more ..... } } @inproceedings{ieeebib380, title={ Particle swarm optimisation for evolving artificial neural network}, author = {Chunkai Zhang and Huihe Shao and Yu Li}, booktitle={2000 IEEE International Conference on Systems, Man, and Cybernetics}, notes={Volume 4, 8-11 Oct. 2000}, year={2000}, pages={2487 - 2490 vol.4}, abstract={The information processing capability of artificial neural networks (ANNs) is closely related to its architecture and weights. The paper describes a new evolutionary system for evolving artificial feedforward neural networks, which is based on the pa..... } } @inproceedings{ieeebib381, title={ Empirical study of particle swarm optimization}, author = {Y. Shi and R.C. Eberhart}, booktitle={Proceedings of the 1999 Congress on Evolutionary Computation, 1999. CEC 99}, notes={Volume 3, 6-9 July 1999}, year={1999}, pages={ }, abstract={We empirically study the performance of the particle swarm optimizer (PSO). Four different benchmark functions with asymmetric initial range settings are selected as testing functions. The experimental results illustrate the advantages and disadvanta..... } } @inproceedings{ieeebib382, title={ The swarm and the queen: towards a deterministic and adaptive particle swarm optimization}, author = {M. Clerc}, booktitle={Proceedings of the 1999 Congress on Evolutionary Computation, 1999. CEC 99}, notes={Volume 3, 6-9 July 1999}, year={1999}, pages={ }, abstract={A very simple particle swarm optimization iterative algorithm is presented, with just one equation and one social/confidence parameter. We define a no-hope convergence criterion and a rehope method so that, from time to ti..... } } @inproceedings{ieeebib383, title={ Particle swarm optimiser with neighbourhood operator}, author = {P.N. Suganthan}, booktitle={Proceedings of the 1999 Congress on Evolutionary Computation, 1999. CEC 99}, notes={Volume 3, 6-9 July 1999}, year={1999}, pages={ }, abstract={In recent years population based methods such as genetic algorithms, evolutionary programming, evolution strategies and genetic programming have been increasingly employed to solve a variety of optimisation problems. Recently, another novel populatio..... } } @inproceedings{ieeebib384, title={ The particle swarm: social adaptation of knowledge}, author = {J. Kennedy}, booktitle={IEEE International Conference on Evolutionary Computation, 1997.}, notes={13-16 April 1997}, year={1997}, pages={303 - 308}, abstract={Particle swarm adaptation is an optimization paradigm that simulates the ability of human societies to process knowledge. The algorithm models the exploration of a problem space by a population of individuals; individuals' successes influence their s..... } } @article{ieeebibJ385, title={ Comparison of Different Heuristic Optimization Methods for Near-Field Antenna Measurements}, author={Jess Ramn Prez and Jos Basterrechea}, journal={IEEE Transactions on Antennas and Propagation}, volume= 55, issue= 3, date={}, part1={ March 2007 Page(s):549 - 555 }, year=2007, abstract={A comparison between different modern heuristic optimization methods applied to antenna far-field radiation pattern reconstruction from planar near-field data is presented in this paper. The antenna under test is represented by means of equivalent ma..... } } @article{ieeebibJ386, title={ Application of Artificial Neural Networks to Broadband Antenna Design Based on a Parametric Frequency Model}, author={Youngwook Kim and Sean Keely and Joydeep Ghosh and Hao Ling}, journal={IEEE Transactions on Antennas and Propagation}, volume= 55, issue= 3, date={}, part1={ March 2007 Page(s):669 - 674 }, year=2007, abstract={An artificial neural network (ANN) is proposed to predict the input impedance of a broadband antenna as a function of its geometric parameters. The input resistance of the antenna is first parameterized by a Gaussian model, and the ANN is constructed..... } } @article{ieeebibJ387, title={ An Effective PSO-Based Memetic Algorithm for Flow Shop Scheduling}, author={Bo Liu and Ling Wang and Yi-Hui Jin}, journal={IEEE Transactions on Systems, Man and Cybernetics, Part B}, volume= 37, issue= 1, date={ Feb. 2007}, pages={18 - 27 }, year={2007}, abstract={This paper proposes an effective particle swarm optimization (PSO)-based memetic algorithm (MA) for the permutation flow shop scheduling problem (PFSSP) with the objective to minimize the maximum completion time, which is a typical non-deterministic ..... } } @article{ieeebibJ388, title={ Inversion of Phaseless Total Field Data Using a Two-Step Strategy Based on the Iterative Multiscaling Approach}, author={G. Franceschini and M. Donelli and R. Azaro and A. Massa}, journal={IEEE Transactions on Geoscience and Remote Sensing}, volume= 44, issue= 12, date={ Dec. 2006}, pages={3527 - 3539 }, year={2006}, abstract={In this paper, a new approach for the quantitative electromagnetic imaging of unknown scatterers located in free space from amplitude-only measurements of the total field is proposed and discussed. The reconstruction procedure splits the problem into..... } } @article{ieeebibJ389, title={ Scalable Model of On-Wafer Interconnects for High-Speed CMOS ICs}, author={Xiaomeng Shi and Kiat Seng Yeo and Jian-Guo Ma and Manh Anh Do and Erping Li}, journal={IEEE Transactions on [see also Components, Packaging and Manufacturing Technology, Part B: Advanced Packaging, IEEE Transactions on] Advanced Packaging}, volume= 29, issue= 4, date={ Nov. 2006}, pages={770 - 776 }, year={2006}, abstract={This paper describes the development of an equivalent circuit model of on-wafer interconnects for high-speed CMOS integrated circuits. By strategically cascading two-pi blocks together, the lumped model can characterize the distributed effects. Besid..... } } @inproceedings{ieeebib39, title={ Hybrid Algorithm Combining Ant Colony Optimization Algorithm with Particle Swarm Optimization}, author = {Gao Shang and Jiang Xin-zi and Tang Kezong and Yang Jingyu}, booktitle={Chinese Control Conference, 2006}, year={2006}, notes={Aug. 2006}, pages={1428 - 1432 }, abstract={By use of the properties of ant colony algorithm and particle swarm optimization, a hybrid algorithm is proposed to solve the traveling salesman problems. First, it adopts statistics method to get several initial better solutions and in accordance wi..... } } @inproceedings{ieeebib390, title={ Synthesis of a Prefractal Dual-Band Monopolar Antenna for GPS Applications}, author = {R. Azaro and F.D. Natale and M. Donelli and E. Zeni and A. Massa}, booktitle={Antennas and Wireless Propagation Letters}, notes={Volume 5, Issue 1, Dec. 2006}, year={2006}, pages={361 - 364 }, abstract={In this letter, the design of a monopolar dual-band antenna operating in the $L1$ and $L2 GPS$ bands is presented. The prefractal geometry of the antenna has been synthesized by means of a particle swarm algorithm for optimizing the values of the ele..... } } } @article{ieeebibJ391, title={ Inversion of ocean color observations using particle swarm optimization}, author={W.H. Slade and H.W. Ressom and M.T. Musavi and R.L. Miller}, journal={IEEE Transactions on Geoscience and Remote Sensing}, volume= 42, issue= 9, date={ Sept. 2004}, pages={1915 - 1923 }, year={2004}, abstract={Inversion of ocean color reflectance measurements can be cast as an optimization problem, where particular parameters of a forward model are optimized in order to make the forward-modeled spectral reflectance match the spectral reflectance of a given..... } } @article{ieeebibJ392, title={ Automatic PMD compensation experiment with particle swarm optimization and adaptive dithering algorithms for 10-gb/s NRZ and RZ formats}, author = {Yuan Zheng and Xiaoguang Zhang and Guangtao Zhou and Yu Shen and Lin Chen and Li Yu and Lixia Xi and Bojun Yang}, journal={IEEE Journal of Quantum Electronics}, notes={Volume 40, Issue 4, April 2004}, year={2004}, pages={427 - 435 }, abstract={We demonstrate a 10-Gb/s polarization-mode dispersion (PMD) compensation experiment by using a 4-degree of freedom compensator for both NRZ and RZ formats. The particle swarm optimization method is used as the searching algorithm and an adaptive dith..... } } @inproceedings{ieeebib393, title={ Wavelength detection in FBG sensor network using tree search DMS-PSO}, author = {J.J. Liang and P.N. Suganthan and C.C. Chan and V.L. Huang}, booktitle={Photonics Technology Letters, IEEE}, notes={Volume 18, Issue 12, June 2006}, year={2006}, pages={1305 - 1307 }, abstract={As the number of fiber Bragg gratings (FBGs) increases, the conventional peak detection method will be unsuitable to detect Bragg wavelengths of FBG sensors in a wavelength-division-multiplexed (WDM) network. To solve this problem while achieving a h..... } } @inproceedings{ieeebib394, title={ Particle swarm optimization used as a control algorithm for adaptive PMD compensation}, author = {Xiaoguang Zhang and Yuan Zheng and Yu Shen and Jianzhong Zhang and Bojun Yang}, booktitle={Photonics Technology Letters, IEEE}, notes={Volume 17, Issue 1, Jan. 2005}, year={2005}, pages={85 - 87 }, abstract={We introduce particle swarm optimization (PSO) into adaptive polarization-mode dispersion (PMD) compensation in a 40-Gb/s optical time-division-multiplexing communication system. In the searching process for automatic PMD compensation, the PSO algori..... } } @article{ieeebibJ395, title={ Multiswarms, exclusion, and anti-convergence in dynamic environments}, author={T. Blackwell and J. Branke}, journal={IEEE Transactions on Evolutionary Computation}, volume= 10, issue= 4, date={ Aug. 2006}, pages={459 - 472 }, year={2006}, abstract={Many real-world problems are dynamic, requiring an optimization algorithm which is able to continuously track a changing optimum over time. In this paper, we explore new variants of particle swarm optimization (PSO) specifically designed to work well..... } } @article{ieeebibJ396, title={ Locating and tracking multiple dynamic optima by a particle swarm model using speciation}, author={D. Parrott and Xiaodong Li}, journal={IEEE Transactions on Evolutionary Computation}, volume= 10, issue= 4, date={ Aug. 2006}, pages={440 - 458 }, year={2006}, abstract={This paper proposes an improved particle swarm optimizer using the notion of species to determine its neighborhood best values for solving multimodal optimization problems and for tracking multiple optima in a dynamic environment. In the proposed spe..... } } @article{ieeebibJ397, title={ A particle swarm optimization for economic dispatch with nonsmooth cost functions}, author={Jong-Bae Park and Ki-Song Lee and Joong-Rin Shin and K.Y. Lee}, journal={IEEE Transactions on Power Systems}, volume= 20, issue= 1, date={ Feb. 2005}, pages={34 - 42 }, year={2005}, abstract={This work presents a new approach to economic dispatch (ED) problems with nonsmooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have nonsmooth cost functions with equality and inequality constraints t..... } } @article{ieeebibJ398, title={ Particle swarm optimization to solving the economic dispatch considering the generator constraints}, author={Zwe-Lee Gaing}, journal={IEEE Transactions on Power Systems}, volume= 18, issue= 3, date={ Aug. 2003}, pages={1187 - 1195 }, year={2003}, abstract={This paper proposes a particle swarm optimization (PSO) method for solving the economic dispatch (ED) problem in power systems. Many nonlinear characteristics of the generator, such as ramp rate limits, prohibited operating zone, and nonsmooth cost f..... } } @article{ieeebibJ399, title={ A particle swarm optimization for reactive power and voltage control considering voltage security assessment}, author={H. Yoshida and K. Kawata and Y. Fukuyama and S. Takayama and Y. Nakanishi}, journal={IEEE Transactions on Power Systems}, volume= 15, issue= 4, date={ Nov. 2000}, pages={1232 - 1239 }, year={2000}, abstract={This paper presents a particle swarm optimization (PSO) for reactive power and voltage control (volt/VAr control: VVC) considering voltage security assessment (VSA). VVC can be formulated as a mixed-integer nonlinear optimization problem (MINLP). The..... } } @inproceedings{ieeebib4, title={ A Hybrid Optimized Algorithm Based on Improved Simplex Method and Particle Swarm Optimization}, author = {Junfeng Chen and Ziwu Ren and Xinnan Fan}, booktitle={Chinese Control Conference, 2006}, year={2006}, notes={Aug. 2006}, pages={1448 - 1453}, abstract={Aiming at the problem that the particle swarm optimization is difficult to deal with local convergence and premature problem, a hybrid computational algorithm based on an improved simplex method and particle swarm optimization has been presented in t..... } } @inproceedings{ieeebib40, title={ Particle Swarm Optimization based on Dynamic Niche Technology with Applications to Conceptual Design}, author = {Xiyu Liu and Hong Liu and Huichuan Duan}, booktitle={Computer Supported Cooperative Work in Design, 10th International Conference on}, notes={May 2006}, year={2006}, pages={1 - 6 }, abstract={Based on the standard particle swarm optimization (PSO) algorithm together with the widely used dynamic niche technology, this paper presents a new variation combined with the dynamic niche sharing technique on the basis of traditional PSO algorithm...... } } @article{ieeebibJ400, title={ Use of intelligent-particle swarm optimization in electromagnetics}, author={G. Ciuprina and D. Ioan and I. Munteanu}, journal={IEEE Transactions on Magnetics}, volume= 38, issue= 2, date={}, part1={ March 2002 Page(s):1037 - 1040 }, abstract={The paper describes a new stochastic heuristic algorithm for global optimization. The new optimization algorithm, called intelligent-particle swarm optimization (IPSO), offers more intelligence to particles by using concepts such as: group experience..... } } @article{ieeebibJ401, title={ Particle swarm optimization - mass-spring system analogon}, author={B. Brandstatter and U. Baumgartner}, journal={IEEE Transactions on Magnetics}, volume= 38, issue= 2, date={}, part1={ March 2002 Page(s):997 - 1000 }, abstract={A concept for the optimization of nonlinear cost functionals, occurring in electrical engineering applications, using particle swarm optimization (PSO) is proposed. PSO is a stochastic optimization technique, whose stochastic behavior can be controll..... } } @article{ieeebibJ402, title={ Pareto optimality and particle swarm optimization}, author={U. Baumgartner and Ch. Magele and W. Renhart}, journal={IEEE Transactions on Magnetics}, volume= 40, issue= 2, date={}, part2={ March 2004 Page(s):1172 - 1175 }, abstract={Real-world optimization problems often require the minimization/maximization of more than one objective, which, in general, conflict with each other. These problems (multiobjective optimization problems, vector optimization problems) are usually trea..... } } @article{ieeebibJ403, title={ Particle swarm optimization in electromagnetics}, author={J. Robinson and Y. Rahmat-Samii}, journal={IEEE Transactions on Antennas and Propagation}, volume= 52, issue= 2, date={ Feb. 2004}, pages={397 - 407 }, year={2004}, abstract={The particle swarm optimization (PSO), new to the electromagnetics community, is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarms. This paper introduces a conceptual overview and detailed explana..... } } @article{ieeebibJ404, title={ A hybrid of genetic algorithm and particle swarm optimization for recurrent network design}, author={Chia-Feng Juang}, journal={IEEE Transactions on Systems, Man and Cybernetics, Part B}, volume= 34, issue= 2, date={ April 2004}, pages={997 - 1006 }, year={2004}, abstract={An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid of genetic algorithm ..... } } @article{ieeebibJ405, title={ Efficiency-Constrained Particle Swarm Optimization of a Modified Bernstein Polynomial for Conformal Array Excitation Amplitude Synthesis}, author={D.W. Boeringer and D.H. Werner}, journal={IEEE Transactions on Antennas and Propagation}, volume= 53, issue= 8, date={}, part2={ Aug. 2005 Page(s):2662 - 2673 }, year={2005}, abstract={As various enabling technologies advance, conformal phased arrays are finding more numerous applications. Because a conformal array is curved, new far field pattern behaviors emerge and many of the traditional linear and planar phased array synthesis..... } } @article{ieeebibJ406, title={ Particle swarm optimization and finite-element based approach for microwave filter design}, author={Wen Wang and Yilong Lu and J.S. Fu and Yong Zhong Xiong}, journal={IEEE Transactions on Magnetics}, volume= 41, issue= 5, date={ May 2005}, pages={1800 - 1803 }, year={2005}, abstract={A novel approach is proposed for compact planar microwave filter design. The powerful particle swarm optimization (PSO) and finite-element method (FEM) are combined together to allow optimal filter design with arbitrary geometries. This approach is m..... } } @inproceedings{ieeebib407, title={ Design of Yagi-Uda antennas using comprehensive learning particle swarm optimisation}, author = {S. Baskar and A. Alphones and P.N. Suganthan and J.J. Liang}, booktitle={Microwaves, Antennas and Propagation, IEE Proceedings -}, notes={Volume 152, Issue 5, 7 Oct. 2005}, year={2005}, pages={340 - 346 }, abstract={A method of using particle swarm optimisation (PSO) algorithms to optimise the element spacing and lengths of Yagi-Uda antennas is presented. SuperNEC, an object-oriented version of the numerical electromagnetic code (NEC-2) is used to evaluate the p.....} } @inproceedings{ieeebib408, title={ Evolutionary fuzzy control of flexible AC transmission system}, author = {Chun-Feng Lu and Chia-Feng Juang}, booktitle={Generation, Transmission and Distribution, IEE Proceedings-}, notes={Volume 152, Issue 4, 8 July 2005}, year={2005}, pages={441 - 448 }, abstract={A fuzzy-controller design by the hybrid of genetic algorithm and particle-swarm optimisation (F-HGAPSO) is employed for a thyristor-controlled series capacitor (TCSC) to improve the transient stability of flexible AC transmission systems (FACTS). Acc.....} } @inproceedings{ieeebib409, title={ Particle Swarm Optimisation for Economic Dispatch with Cubic Fuel Cost Function}, author = {T. Adhinarayanan and Maheswarapu Sydulu}, booktitle={TENCON 2006. 2006 IEEE Region 10 Conference}, notes={Nov. 2006}, year={2006}, pages={1 - 4 }, abstract={This paper presents an efficient and reliable particle swarm optimisation (PSO) algorithm for solving the economic dispatch (ED) problems with smooth cost functions as well as cubic fuel cost functions. The practical ED problems have nonsmooth cost f..... } } @inproceedings{ieeebib41, title={ Solving Constrained Optimization Problems by the ýý Constrained Particle Swarm Optimizer with Adaptive Velocity Limit Control}, author = {T. Takahama and S. Sakai}, booktitle={2006 IEEE Conference on Cybernetics and Intelligent Systems}, note={June 2006}, year={2006}, pages={1 - 7 }, abstract={The epsiv constrained method is an algorithm transformation method, which can convert algorithms for unconstrained problems to algorithms for constrained problems using the epsiv level comparison that compares the search points based on the constrain..... } } @inproceedings{ieeebib410, title={ Obstacle-avoidance Path Planning for Soccer Robots Using Particle Swarm Optimization}, author = {Li Wang and Yushu Liu and Hongbin Deng and Yuanqing Xu}, booktitle={2006. ROBIO '06. IEEE International Conference on Robotics and Biomimetics}, notes={Dec. 2006}, year={2006}, pages={1233 - 1238}, abstract={Optimal path planning for mobile robots plays an important role in the field of robotics. At present, there are many advanced algorithms used to solve this optimization problem. In this paper a dynamic obstacle-avoidance path planning approach for so..... } } @inproceedings{ieeebib411, title={ Global Generator and Transmission Maintenance Scheduling Based On a Mixed Intelligent Optimal Algorithm in Power Market}, author = {Jun Shu and Lizi Zhang and Bing Han and Xianchao Huang}, booktitle={International Conference on Power System Technology, 2006. PowerCon 2006}, notes={Oct. 2006}, year={2006}, pages={1 - 5 }, abstract={This paper presents a mathematical model of coordination and optimization of generator and transmission maintenance in power market. In this model, security and economical efficiency of power system and fairness of power market are taken into account..... } } @inproceedings{ieeebib412, title={ Application of multi-objective algorithm based on particle swarm optimization in electrical short-term load forecasting}, author = {Li Feng and Jianjun He and Qingyun Kong and Lin Guo}, booktitle={International Conference on Power System Technology, 2006. PowerCon 2006}, notes={Oct. 2006}, year={2006}, pages={1 - 5 }, abstract={Based on the knowledge of historical data sets, a fuzzy rule-based classifier for electrical load pattern classification is set up. Considering with the accuracy and interpretation of fuzzy rules, multi-objective particle swarm optimization are appli..... } } @inproceedings{ieeebib413, title={ Chaotic Particle Swarm Optimization Method Exploiting Sinusoidal Perturbations}, author = {K. Tatsumi and S. Sasaki and T. Tanino}, booktitle={SICE-ICASE, 2006. International Joint Conference}, notes={Oct. 2006}, year={2006}, pages={6013 - 6016 }, abstract={The particle swarm optimization (PSO) method is a population-based optimization technique which searches for solutions by updating simultaneously a number of candidate solutions called particles. Since, in the PSO, the exploration ability is importan..... } } @inproceedings{ieeebib414, title={ Particle Swarm Optimization for Identification of GMS Friction Model}, author = {I. Nilkhamhang and A. Sano}, booktitle={SICE-ICASE, 2006. International Joint Conference}, notes={Oct. 2006}, year={2006}, pages={5628 - 5633 }, abstract={This paper addresses the identification problem of the generalized Maxwell-slip (GMS) friction model. The GMS model is a dynamic friction representation capable of describing essential friction characteristics. However, the identification process is ..... } } @inproceedings{ieeebib415, title={ Nonlinear System Identification based on Support Vector Machine using Particle Swarm Optimization}, author = {Byung-hwa Lee and Sang-un Kim and Jin-wook Seok and Sangchul Won}, booktitle={SICE-ICASE, 2006. International Joint Conference}, notes={Oct. 2006}, year={2006}, pages={5614 - 5618 }, abstract={This paper describes a different method for the identification of the nonlinear system and parameter optimization of the obtained input-output model. The approach is the technique using the least square support vector machines(LS-SVM) regression base..... } } @inproceedings{ieeebib416, title={ Reinforcement Learning through Interaction among Multiple Agents}, author = {H. Iima and Y. Kuroe}, booktitle={SICE-ICASE, 2006. International Joint Conference}, notes={Oct. 2006}, year={2006}, pages={2457 - 2462 }, abstract={In ordinary reinforcement learning algorithms, a single agent learns to achieve a goal through many episodes. If a learning problem is complicated, it may take a much computation time to obtain the optimal policy. Meanwhile, for optimization problems..... } } @inproceedings{ieeebib417, title={ Development of Golden Section Search Driven Particle Swarm Optimization and its Application}, author = {Sehoon Oh and Yoichi Hori}, booktitle={SICE-ICASE, 2006. International Joint Conference}, notes={Oct. 2006}, year={2006}, pages={2868 - 2873 }, abstract={The Particle Swarm Optimization (PSO), although it has been widely used in various fields, has a step-size problem, which deteriorates optimization performance. This problem is resolved using the Golden Section Search (GSS) and the Steepest descent m..... } } @inproceedings{ieeebib418, title={ A study of Particle Swarm Optimization in Urban Traffic Surveillance System}, author = {Jianming Hu and Jingyan Song and Xiaojing Kang and Mingchen Zhang}, booktitle={IMACS Multiconference on Computational Engineering in Systems Applications}, notes={Oct. 2006}, year={2006}, pages={2056 - 2061 }, abstract={This paper presents our recent research on topology planning of the Urban Traffic Surveillance System (UTSS). Based on the proposed wireless sensor networks in UTSS, Particle Swarm Optimization (PSO) method is applied to deal with the node optimizati..... } } @inproceedings{ieeebib419, title={ Training Bao Game-Playing Agents using Coevolutionary Particle Swarm Optimization}, author = {J. Conradie and A.P. Engelbrecht}, booktitle={2006 IEEE Symposium on Computational Intelligence and Games}, notes={May 2006}, year={2006}, pages={67 - 74 }, abstract={Bao, an African board game of the Mancala family, is a complex two-player game with a very large search space and complex rule set. The success of game tree approaches to create game-playing agents rests heavily on the, usually handcrafted, static ev..... } } @inproceedings{ieeebib42, title={ Performance of two Improved Particle Swarm Optimization In Dynamic Optimization Environments}, author = {Guanyu Pan and Quansheng Dou and Xiaohua Liu}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={1024 - 1028 }, abstract={The particle swarm optimization (PSO) was originally designed by Kennedy and Eberhart in 1995 and has been applied successfully in solving various optimization problems. The PSO idea is inspired by natural concepts such as fish schooling, bird flocki..... } } @inproceedings{ieeebib420, title={ Character Recognition Based on Hierarchical RBF Neural Networks}, author = {Yuelong Li and Jinping Li and Li Meng}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 1, Oct. 2006}, year={2006}, pages={127 - 132 }, abstract={When algorithms extracting and recognizing characters from text image is devised, the time loss and recognizing quality are two of the most important properties taken into account. To achieve high recognition performance in both of them, we provide a..... } } @inproceedings{ieeebib421, title={ Improved Particle Swarm Optimization Algorithm for Stochastic EOQ Models with Multi-Item and Multi-Storehouse}, author = {Peixin Zhao and Hong Wang and Hongfeng Gao}, booktitle={2006 IEEE International Conference on Information Acquisition}, notes={Aug. 2006}, year={2006}, pages={1047 - 1051}, abstract={A new economic order quantity (EOQ) model is developed for multi-item and multi-storehouse with limited funds, limited storage capacity and stochastic demand. The model is proved to be a nonlinear convex programming. For finding the optimal replenish..... } } @inproceedings{ieeebib422, title={ Density Estimation Using a Generalized Neuron}, author = {R. Kiran and G.K. Venayagamoorthy and M. Palaniswami}, booktitle={9th International Conference on Information Fusion, 2006. ICIF '06}, notes={July 2006}, year={2006}, pages={1 - 7 }, abstract={Neural networks have been shown to be useful tools for density estimation. However, the training of neural network structures is time consuming and requires fast processors for practical applications. A new method with a generalized neuron (GN) for d..... } } @inproceedings{ieeebib423, title={ A Multi-Agent Particle Swarm Optimization Framework with Applications}, author = {Xiyu Liu and Ke Xu and Hong Liu}, booktitle={2006 1st International Symposium on Pervasive Computing and Applications}, notes={Aug. 2006}, year={2006}, pages={1 - 6 }, abstract={The traditional particle swarm optimization technique is incorporated with multi-agent systems. A new PSO framework HMAS is presented with particles as agents. Actions and properties of agents are defined. We also present a test application in cluste..... } } @inproceedings{ieeebib424, title={ A Fuzzy Adaptive Programming Method of Particle Swarm Optimization}, author = {Qi Kang and Lei Wang and Qidi Wu}, booktitle={TENCON 2005 2005 IEEE Region 10}, notes={Nov. 2005}, year={2005}, pages={1 - 6 }, abstract={This paper introduces a novel multi-optimum programming mode for the particle swarm optimization algorithm. Initially, to efficiently control the relationship between multi-optimum information and convergence to the global optimum solution, fuzzy log..... } } @inproceedings{ieeebib425, title={ A Scheduling Holon Modeling Method with Petri Net and its Optimization with a Novel PSO-GA Algorithm}, author = {Fuqing Zhao and Qiuyu Zhang and Yahong Yang}, booktitle={10th International Conference on Computer Supported Cooperative Work in Design}, notes={May 2006}, year={2006}, pages={1 - 6 }, abstract={Holonic manufacturing systems (HMS) provide a flexible and decentralized manufacturing environment to accommodate changes dynamically. This paper presents a framework to model and control HMS based on Petri net and MAS theory. A time Petri net (TPN) ..... } } @inproceedings{ieeebib426, title={ Simultaneous Localization and Mapping with Particle Swarm Localization}, author = {B. Todor and D. Darabos}, booktitle={The Third Workshop 2005 IEEE Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, Proceedings of}, notes={Sept. 2005}, year={2005}, pages={216 - 221 }, abstract={In this article the authors present a Simultaneous Localization and Mapping (SLAM) method based on probability distribution function matching. The algorithm randomly samples the posteriori pdf based on the reverse models of the range sensors, and the..... } } @inproceedings{ieeebib427, title={ Economic Dispatch with Environmental Considerations using Particle Swarm Optimization}, author = {M.R. AlRashidi and M.E. El-Hawary}, booktitle={2006 Large Engineering Systems Conference on Power Engineering}, notes={July 2006}, year={2006}, pages={41 - 46 }, abstract={This paper presents a Particle Swarm Optimization (PSO) algorithm to solve an Economic-Emission Dispatch problem (EED). This problem has been getting more attention recently due to the deregulation of the power industry and strict environmental regul..... } } @inproceedings{ieeebib428, title={ Particle Swarm Optimization for Antenna Far-Field Radiation Pattern Reconstruction}, author = {J.R. Perez and J. Basterrechea}, booktitle={Microwave Conference, 2006. 36th European}, notes={Sept. 2006}, year={2006}, pages={687 - 690 }, abstract={A particle swarm optimization (PSO) based algorithm applied to antenna far-field radiation pattern prediction from planar near-field samples is presented. The radiation of the antenna is modeled using equivalent magnetic currents (EMC) whose componen..... } } @inproceedings{ieeebib429, title={ Emission-Economic Dispatch using a Novel Constraint Handling Particle Swarm Optimization Strategy}, author = {M.R. AlRashidi and M. E. El-Hawary}, booktitle={Canadian Conference on Electrical and Computer Engineering}, notes={May 2006}, year={2006}, pages={664 - 669 }, abstract={This paper presents a Particle Swarm Optimization (PSO) algorithm to solve an Economic-Emission Dispatch problem (EED) which gained recent attention due to the deregulation of the power industry and strict environmental regulations. The problem treat..... } } @inproceedings{ieeebib43, title={ Identification of convection heat transfer coefficient parameters based on hybrid particle swarm algorithm in the secondary cooling zone for steel continuous casting process}, author = {Guo-Hua Wu and Rong-Yang Wu}, booktitle={2005 ICSC Congress on Computational Intelligence Methods and Applications}, notes={15-17 Dec. 2005}, year={2005}, pages={6 pp. }, abstract={Solidification model is developed based on control volume method for steel continuous casting process, which is nonlinear and non-differential, and parameters of convective heat transfer coefficient for each segment of the secondary cooling zone are ..... } } @inproceedings{ieeebib430, title={ Security-Constrained Unit Commitment using Particle Swarms}, author = {R. Collett and J. Quaicoe}, booktitle={Canadian Conference on Electrical and Computer Engineering}, notes={May 2006}, year={2006}, pages={1125 - 1129 }, abstract={This investigation presents a novel approach for solving security-constrained unit commitment (SCUC) problems. These problems involve the development of generation schemes for a power system while adhering to a set of operational constraints. As SCUC..... } } @inproceedings{ieeebib431, title={ Particle Swarm Optimization for Constrained Portfolio Selection Problems}, author = {Wei Chen and Run-Tong Zhang and Yong-Ming Cai and Fa-Sheng Xu}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={2425 - 2429 }, abstract={Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions, modern portfolio theory is based on a rational investor choosing the proportions of assets in a portfolio so as to minimiz..... } } @inproceedings{ieeebib432, title={ An Improved Particle Swarm Optimization(PSO) Algorithm and Fuzzy Inference Systems Based Approach to Process Planning and Production Scheduling Integration in Holonic Manufacturing System (HMS)}, author = {Fu-Qing Zhao and Qiu-Yu Zhang and Ya-Hong Yang}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={396 - 401 }, abstract={New paradigms for manufacturing system control are required that provide manufacturers with the adaptability and responsiveness required to compete in today's market. In this paper, an integrated process planning and scheduling system, which is appli..... } } @inproceedings{ieeebib433, title={ Nonlinear Neural Network Predictive Control for Power Unit using Particle Swarm Optimization}, author = {Jian-Mei Xiao and Xi-Huai Wang}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={2851 - 2856 }, abstract={A novel approach of nonlinear model predictive control (NMPC) is proposed using radial basis function neural network (RBFNN) and particle swarm optimization (PSO). A multi-step predictive model of the controlled process based on RBFNN is studied. The..... } } @inproceedings{ieeebib434, title={ Direct Torque Control Mining Locomotive Haulage with Fuzzy Controller Based on Particle Swarm Optimization}, author = {Xian-Min Ma and Yan-Yun Zhao}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={505 - 510 }, abstract={A novel approach is proposed to design an optimal fuzzy controller via particle swarm optimization in this paper. The main idea of the proposed method is to find the suitable fuzzy controller parameters according to the performance index of the syste..... } } @inproceedings{ieeebib435, title={ An Effective Clustering Method Using a Discrete Particle Swarm Optimization Algorithm-Based Hybrid Approach}, author = {Jing-Hua Guan and Da-You Liu and Hai-Yang Jia and Peng Yu}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={1114 - 1119 }, abstract={The purpose of this paper is to present and evaluate an improved Naive Bayes algorithm for clustering. Many researchers search for parameter values using EM algorithm. It is well-known that EM approach has a drawback ýý local optimal solution, so we ..... } } @inproceedings{ieeebib436, title={ A Novel Particle Swarm Optimization Algorithm for Solving Transportation Problem}, author = {Zhi-Feng Hao and Han Huang and Xiao-Wei Yang}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={2178 - 2183 }, abstract={The transportation problem (TP) is well known as a basic network problem for it could be extensively applied in many fields. The linear transportation problem (LTP), which is the core and basic model of TP, can be extended to other TP with higher com..... } } @inproceedings{ieeebib437, title={ An Analysis Of PSO Hybrid Algorithms For Feed-Forward Neural Networks Training}, author = {M. Carvalho and T.B. Ludermir}, booktitle={Ninth Brazilian Symposium on Neural Networks, 2006. SBRN '06}, notes={Oct. 2006}, year={2006}, pages={2 - 2 }, abstract={Training neural networks is a complex task of great importance in problems of supervised learning. The Particle Swarm Optimization (PSO) consists of a stochastic global search originated from the attempt to graphically simulate the social behavior of..... } } @inproceedings{ieeebib438, title={ Particle Swarm Optimisation for the Design of Brushless Permanent Magnet Machines}, author = {R. Wrobel and P.H. Mellor}, booktitle={The 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting, Conference Record of}, notes={Volume 4, Oct. 2006}, year={2006}, pages={1891 - 1897 }, abstract={This paper describes the use of a particle swarm optimisation (PSO) algorithm in the design optimisation of two surface magnet brushless machines. Two PSO algorithms are presented: the global best PSO (gbest PSO) and local best PSO (lbest PSO). The a..... } } @inproceedings{ieeebib439, title={ An Improved Particle Swarm Optimization-Based Approach for Production Scheduling Problems}, author = {Fuqing Zhao and Qiuyu Zhang and Yahong Yang}, booktitle={Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation}, notes={June 2006}, year={2006}, pages={2279 - 2283}, abstract={Job-shop scheduling problem(JSSP) is very common in a discrete manufacturing environment. It deals with multi-operation models, which are different from the flow shop models. It is usually very hard to find its optimal solution. In this paper, a new ..... } } @inproceedings{ieeebib44, title={ Fuzzy logic controlled particle swarm for reactive power optimization considering voltage stability}, author = {W. Zhang and Y. Liu}, booktitle={Power Engineering Conference, 2005. IPEC 2005. The 7th International}, notes={29 Nov.-2 Dec. 2005}, year={2005}, pages={ }, abstract={This paper presents the application of a fuzzy logic controlled particle swarm optimization (FLCPSO) to reactive power and voltage control (Volt/VAR control or VVC) considering voltage stability. An improved particle swarm optimization with three fuz..... } } @inproceedings{ieeebib440, title={ Design of a fast transient stability control scheme in power system}, author = {Zhihong Yu and Xiaoxin Zhou and Zhongxi Wu}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={8 pp. }, abstract={This paper describes the optimization of the settings for various emergency controls in an electrical power system, which is done by PSASP Lab of CEPRI. The aim is to regain a state of operating equilibrium when the power system is subjected to distu..... } } @inproceedings{ieeebib441, title={ Intelligent techniques applied to power plant}, author = {K.Y. Lee}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={8 pp. }, abstract={Developments in power plant control are increasing steadily in recent years by seeking new techniques other than conventional PID controls. This panel introduces intelligent techniques to power plant control, which deal with complex dynamic systems h..... } } @inproceedings{ieeebib442, title={ Optimal design of power system stabilizers using a small population based PSO}, author = {T.K. Das and G.K. Venayagamoorthy}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={7 pp. }, abstract={Power system stabilizers (PSSs) are used to generate supplementary control signals to excitation systems in order to damp out local and inter-area oscillations. In this paper, a modified particle swarm optimization (PSO) algorithm with a small popula..... } } @inproceedings{ieeebib443, title={ An optimum reactance one-port compensator for harmonic mitigation}, author = {E.F. El-Saadany and H.H. Zeineldin}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={6 pp. }, abstract={Most facilities employ a variety of devices such as multiple switch mode power supplies, motors, fans, and other nonlinear loads. One of the adverse effects of multiple nonlinear loads is harmonic distortion. Harmonic currents in particular are recei..... } } @inproceedings{ieeebib444, title={ Application of PSO technique to find optimal settings of TCSC for static security enhancement considering installation cost}, author = {S.M.R. Slochanal and M. Saravanan and A.C. Devi}, booktitle={Power Engineering Conference, 2005. IPEC 2005. The 7th International}, notes={29 Nov.-2 Dec. 2005}, year={2005}, pages={ }, abstract={This paper describes the application of particle swarm optimization (PSO) technique to find the optimal setting of thyristor-controlled series capacitors (TCSCs) in order to eliminate or minimize line overloads under single contingency or critical do..... } } @inproceedings{ieeebib445, title={ A robust STATCOM damping controller for a multi-machine power system}, author = {S.F. Faisal and A.H.M.A. Rahim}, booktitle={Power Engineering Conference, 2005. IPEC 2005. The 7th International}, notes={29 Nov.-2 Dec. 2005}, year={2005}, pages={ }, abstract={This paper presents a robust STATCOM controller design for damping transients in a multi-machine power system. The method of multiplicative uncertainty is employed to model the variations in the power system operation. A graphical loop shaping techni..... } } @inproceedings{ieeebib446, title={ High performance iris recognition based on LDA and LPCC}, author = {Chia Te Chu and Ching-Han Chen}, booktitle={2005. ICTAI 05. 17th IEEE International Conference on Tools with Artificial Intelligence}, notes={14-16 Nov. 2005}, year={2005}, pages={5 pp.}, abstract={In this paper, the iris recognition algorithm based on LPCC and LDA is first presented. So far, the two algorithms are not found for iris recognition in literature. In addition, a simple and fast training algorithm, particle swarm optimization (PSO),..... } } @inproceedings{ieeebib447, title={ Obstacle avoidance with multi-objective optimization by PSO in dynamic environment}, author = {Hua-Qing Min and Jin-Hui Zhu and Xi-Jing Zheng}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 5, 18-21 Aug. 2005}, year={2005}, pages={2950 - 2956 Vol. 5 }, abstract={The second order motion model is one of the fundamental questions, a mostly important object in motion planning research of mobile robots, especially in complex environment. Based on the research of the second order motion model, this paper puts forw..... } } @inproceedings{ieeebib448, title={ An improved particle swarm optimization and its application in long-term streamflow forecast}, author = {Fang Liu and Jian-Zhong Zhou and Reng-Cun Fang and Bin Peng and Jun-Jie Yang}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 5, 18-21 Aug. 2005}, year={2005}, pages={2913 - 2918 Vol. 5 }, abstract={An improved PSO based on the Metropolis criterion, called MPSO, is proposed and applied in long-term streamflow forecast. MPSO focuses on the inertia weight of PSO, and leads the inertia weight to adjust in accordance to the direction of global best ..... } } @inproceedings{ieeebib449, title={ Efficient optimization procedures for stochastic simulation systems}, author = {Da-Peng Wu and Ming Lu and Jian-Ping Zhang}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 5, 18-21 Aug. 2005}, year={2005}, pages={2895 - 2900 Vol. 5 }, abstract={In the research presented, we applied the particle swarm optimization (PSO) technique to optimize a concrete delivery operations simulation model (named HKCONSIM), aimed at improving the overall operational efficiency by minimizing the nonproductive ..... } } @inproceedings{ieeebib45, title={ Evolving problems to learn about particle swarm and other optimisers}, author = {W.B. Langdon and R. Poli}, booktitle={The 2005 IEEE Congress on Evolutionary Computation, 2005}, notes={Volume 1, 2-5 Sept. 2005}, year={2005}, pages={81 - 88 Vol.1 }, abstract={We use evolutionary computation (EC) to automatically find problems which demonstrate the strength and weaknesses of modern search heuristics. In particular we analyse particle swarm optimization (PSO) and differential evolution (DE). Both evolutiona..... } } @inproceedings{ieeebib450, title={ Predictive control of proton exchange membrane fuel cell (PEMFC) based on support vector regression machine}, author = {Yuan Ren and Guang-Yi Cao and Xin-Jian Zhu}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 7, 18-21 Aug. 2005}, year={2005}, pages={4028 - 4031 Vol. 7 }, abstract={A new method of the predictive control for proton exchange membrane fuel cell (PEMFC) based on support vector regression machine is presented and the support vector regression machine is constructed. The process plant is modeled on SVRM. The predicti..... } } @inproceedings{ieeebib451, title={ Soft sensing modeling via artificial neural network based on PSO-Alopex}, author = {Shao-Jun Li and Xu-Jie Zhang and Feng Qian}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 7, 18-21 Aug. 2005}, year={2005}, pages={4210 - 4215 Vol. 7 }, abstract={In this paper, algorithm of pattern extraction (Alopex) is introduced into the particle swarm optimization (PSO) to train the artificial neural network (ANN), which is used to construct the soft sensing model. PSO has some significant features such a..... } } @inproceedings{ieeebib452, title={ Distribution network reconfiguration for load balancing using binary particle swarm optimization}, author = {Xiaoling Jin and Jianguo Zhao and Ying Sun and Kejun Li and Boqin Zhang}, booktitle={2004 International Conference on Power System Technology, 2004. PowerCon 2004}, notes={Volume 1, 21-24 Nov. 2004}, year={2004}, pages={507 - 510 Vol.1 }, abstract={In this paper, a method based on modified binary particle swarm optimization (BPSO) is proposed for distribution network reconfiguration with the objective of load balancing. A novel model to simplify distribution network is presented. The feeder rec..... } } @inproceedings{ieeebib453, title={ An improved particle swarm optimization for optimal power flow}, author = {S. He and J.Y. Wen and E. Prempain and Q.H. Wu and J. Fitch and S. Mann}, booktitle={2004 International Conference on Power System Technology, 2004. PowerCon 2004}, notes={Volume 2, 21-24 Nov. 2004}, year={2004}, pages={1633 - 1637 Vol.2 }, abstract={This paper presents an improved particle swarm optimization (PSO) to solve optimal power flow (OPF) problems. The standard PSO algorithm is extended by incorporating a biology concept "passive congregation" to prevent premature convergence and refine..... } } @inproceedings{ieeebib454, title={ Constrained dynamic economic dispatch solution using particle swarm optimization}, author = {Zwe-Lee Gaing}, booktitle={Power Engineering Society General Meeting, 2004. IEEE}, notes={6-10 June 2004}, year={2004}, pages={153 - 158 Vol.1 }, abstract={This paper proposes using the particle swarm optimization (PSO) to solve the constrained dynamic economic dispatch (DED) problem in power system operation. The constrained DED must not only satisfy the system load demand and the spinning reserve capa..... } } @inproceedings{ieeebib455, title={ Particle swarm optimisation for reactive power and voltage control with grid-integrated wind farms}, author = {G. Coath and M. Al-Dabbagh and S.K. Halgamuge}, booktitle={Power Engineering Society General Meeting, 2004. IEEE}, notes={6-10 June 2004}, year={2004}, pages={303 - 308 Vol.1 }, abstract={This paper seeks to apply particle swarm optimisation (PSO) to solve the reactive power and voltage control (RPVC) problem in power systems, considering wind farms (WFs) as one of the power generation sources. PSO is a stochastic optimisation strateg..... } } @inproceedings{ieeebib456, title={ Optimal design for cogging torque reduction of transverse flux permanent motor using particle swarm optimization algorithm}, author = {G.Q. Bao and D. Zhang and J.H. Shi and J.Z. Jiang}, booktitle={Power Electronics and Motion Control Conference, 2004. IPEMC 2004. The 4th International}, notes={Volume 1, 2004}, year={2004}, pages={260 - 263 Vol.1 }, abstract={Great emphasis is paid on transverse flux permanent motors (TFPM) in recent years especially in powerful propulsion system. However, the cogging torque in TFPM leads to mechanical vibration and noise inevitably. This paper presents a new TFPM with co..... } } @inproceedings{ieeebib457, title={ Reactive power optimization based on PSO in a practical power system}, author = {Wen Zhang and Yutian Liu}, booktitle={Power Engineering Society General Meeting, 2004. IEEE}, notes={6-10 June 2004}, year={2004}, pages={239 - 243 Vol.1 }, abstract={This paper presents a particle swarm optimization (PSO) method to deal with reactive power optimization problem in a province power system in China. The objective the optimization problem is to minimize the real power losses whilst maintaining accept..... } } @inproceedings{ieeebib458, title={ A new reactive power optimization algorithm}, author = {A.H. Mantawy and M.S. Al-Ghamdi}, booktitle={Power Tech Conference Proceedings, 2003 IEEE Bologna}, notes={Volume 4, 23-26 June 2003}, year={2003}, pages={6 pp. Vol.4 }, abstract={This paper presents an algorithm for optimizing reactive power using particle swarm algorithm. A new implementation for the particle swarm algorithm has been applied. The objective function of the proposed algorithm is to minimize the system active p..... } } @inproceedings{ieeebib459, title={ Discrete particle swarm optimization algorithm for unit commitment}, author = {Zwe-Lee Gaing}, booktitle={Power Engineering Society General Meeting, 2003, IEEE}, notes={Volume 1, 13-17 July 2003}, year={2003}, pages={ }, abstract={This paper proposes integrating a discrete binary particle swarm optimization (BPSO) method with the Lambda-iteration method for solving unit commitment (UC) problems. The LJC problem is considered as two linked optimization sub-problems: the unit-sc..... } } @inproceedings{ieeebib46, title={ Application of particle swarm optimization in multi-sensor multi-target tracking}, author = {Lei Yang and Weiwei Hu and Shenyuan Yang and Shujin Pu}, booktitle={1st International Symposium on Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006}, notes={19-21 Jan. 2006}, year={2006}, pages={5 pp. }, abstract={For the multi-sensor multi-target data association problem, a novel particle swarm optimization (PSO) algorithm based S-dimensional (S-D) assignment method is proposed in this paper. By a combinational optimal way, it could find the minimum objective..... } } @inproceedings{ieeebib460, title={ Economic load dispatch for nonsmooth cost functions using particle swarm optimization}, author = {Jong-Bae Park and Ki-Song Lee and Joong-Rin Shin and Y. Lee}, booktitle={Power Engineering Society General Meeting, 2003, IEEE}, notes={Volume 2, 13-17 July 2003}, year={2003}, pages={ }, abstract={This paper presents a new approach to economic load dispatch (ELD) problems with nonsmooth objective functions using a particle swarm optimization (PSO). In practice, ELD problems have nonsmooth objective functions with equality and inequality constr..... } } @inproceedings{ieeebib461, title={ A comprehensive method for optimal expansion planning using particle swarm optimization}, author = {P.S. Sensarma and M. Rahmani and A. Carvalho}, booktitle={Power Engineering Society Winter Meeting, 2002. IEEE}, notes={Volume 2, 27-31 Jan. 2002}, year={2002}, pages={1317 - 1322 vol.2 }, abstract={This paper proposes a holistic approach to planning transmission networks. This is necessitated by the need for entrepreneurs to evaluate the costs and returns of a merchant transmission project, before committing actual investment. Most papers addre..... } } @inproceedings{ieeebib462, title={ A particle swarm optimization for reactive power and voltage control considering voltage security assessment}, author = {H. Yoshida and K. Kawata and Y. Fukuyama and S. Takayama and Y. Nakanishi}, booktitle={Power Engineering Society Winter Meeting, 2001. IEEE}, notes={Volume 2, 28 Jan.-1 Feb. 2001}, year={2001}, pages={498 vol.2 }, abstract={Summary form only given, as follows. This paper presents a particle swarm optimization (PSO) for reactive power and voltage control (volt/VAr control: VVC) considering voltage security assessment (VSA). VVC can be formulated as a mixed-integer nonlin..... } } @inproceedings{ieeebib463, title={ Particle swarm optimization for multimachine power system stabilizer design}, author = {A.A. Abido}, booktitle={Power Engineering Society Summer Meeting, 2001. IEEE}, notes={Volume 3, 15-19 July 2001}, year={2001}, pages={1346 - 1351 vol.3 }, abstract={In this paper, a novel evolutionary algorithm based approach to optimal design of multimachine power system stabilizers (PSSs) is proposed. The proposed approach develops and employs particle swarm optimization (PSO) technique to search for optimal s..... } } @inproceedings{ieeebib464, title={ Distribution state estimation considering nonlinear characteristics of practical equipment using hybrid particle swarm optimization}, author = {S. Naka and T. Genji and T. Yura and Y. Fukuyama and N. Hayashi}, booktitle={Proceedings of the International Conference on Power System Technology (PowerCon) 2000}, notes={Volume 2, 4-7 Dec. 2000}, year={2000}, pages={1083 - 1088 vol.2 }, abstract={This paper proposes a distribution state estimation method using a hybrid particle swarm optimization (HPSO). The proposed method considers practical measurements in distribution systems and assumes that absolute values of voltage and current can be ..... } } @inproceedings{ieeebib465, title={ Comparative study between the internal behavior of GA and PSO through problem-specific distance functions}, author = {S.J. Habib and B.S. Al-kazemi}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 3, 2-5 Sept. 2005}, pages={2190 - 2195 Vol. 3 }, abstract={The evolutionary approach is a family of probabilistic search algorithms. The genetic algorithm (GA) and particle swarm optimization (PSO) are members of the evolutionary family, where both GA and PSO have been proven to be successful in finding good..... } } @inproceedings{ieeebib466, title={ Mixed H/spl I.bar/2/H/spl I.bar//spl infin/ optimal PID control for superheated steam temperature system based on PSO optimization}, author = {Pu Han and Yu Huang and Zeng-Zhou Jia and Dong-Feng Wang and Yong-Ling Li}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005}, notes={Volume 2, 18-21 Aug. 2005}, year={2005}, pages={960 - 964 Vol. 2 }, abstract={A general approach is proposed to design a mixed H/spl I.bar/2/H/spl I.bar//spl infin/ optimal PID controller via particle swarm optimization (PSO). The main target of the proposed mixed control method is to find a suitable controller that minimizes ..... } } @inproceedings{ieeebib467, title={ Ultrawideband source localization using a particle-swarm-optimized Capon estimator}, author = {Yifan Chen and V.K. Dubey}, booktitle={2005. ICC 2005. 2005 IEEE International Conference on Communications}, notes={Volume 4, 16-20 May 2005}, year={2005}, pages={2825 - 2829 Vol. 4}, abstract={We present a realistic frequency-dependent channel model for ultrawideband (UWB) communications and develop a generalized broadband Capon estimator for localization of the spatially dispersed UWB signals. The proposed estimator is able to address the..... } } @inproceedings{ieeebib468, title={ Flexible particle swarm optimization tasks for reconfigurable processor arrays}, author = {S. Janson and M. Middendorf}, booktitle={Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium, 2005. }, notes={4-8 April 2005}, year={2005}, pages={8 pp. }, abstract={Multi-task parallel processor arrays are a common machine architecture in which, typically, the tasks running in parallel occupy disjoint subarrays of the machine. On dynamically and partially reconfigurable processor arrays the tasks can be changed ..... } } @inproceedings{ieeebib469, title={ Particle swarm optimization learning fuzzy systems design}, author = {Hsuan-Ming Feng}, booktitle={Third International Conference on Information Technology and Applications, 2005. ICITA 2005}, notes={Volume 1, 4-7 July 2005}, year={2005}, pages={363 - 366 vol.1 }, abstract={A particle swarm optimization (PSO) learning algorithm is proposed in our research to generate fuzzy systems for balancing the car-pole system and approximating a nonlinear function. Trust to the devoted feature of PSO, i.e. simple implementation, fa..... } } @inproceedings{ieeebib47, title={ Adaptive parameter control for quantum-behaved particle swarm optimization on individual level}, author = {Jun Sun and Wenbo Xu and Bin Feng}, booktitle={2005 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 4, 10-12 Oct. 2005}, year={2005}, pages={3049 - 3054 Vol. 4}, abstract={Particle swarm optimization (PSO) is a population-based evolutionary search technique, which has comparable performance with genetic algorithm. The existing PSOs, however, are not global-convergence-guaranteed algorithms. In the previous work, we pro..... } } @inproceedings{ieeebib470, title={ Particle swarm optimization for modeling and parameter extraction of on-chip spiral inductors for RFICs}, author = {S.K. Mandal and A. De and A. Patra and S. Sural and T.K. Bhattacharya}, booktitle={India Annual Conference, 2004. Proceedings of the IEEE INDICON 2004. First}, notes={20-22 Dec. 2004}, year={2004}, pages={17 - 22 }, abstract={In this paper particle swarm optimization (PSO) is used for the design of optimized integrated spiral inductors. A modified compact equivalent circuit model has been developed based on measurement data taken from numerous spiral inductors of differen..... } } @inproceedings{ieeebib471, title={ Worst case circuit design of capacitive sensor electronics with steepest descent particle swarm optimization}, author = {G. Steiner and H. Zangl}, booktitle={2004. IEEE ICIT '04. 2004 IEEE International Conference on Industrial Technology}, notes={Volume 3, 8-10 Dec. 2004}, year={2004}, pages={1198 - 1203 Vol. 3}, abstract={Component tolerances and parameter variations may considerably influence the performance of industrial sensors. Particularly for capacitive sensors, changes of environmental conditions can substantially influence the behavior of the front-end electro..... } } @inproceedings{ieeebib472, title={ Improved particle swarm optimization algorithm for integrated steel-making optimum charge plan}, author = {Yuncan Xue and Xinnan Fan and Wei Jian}, booktitle={Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE}, notes={Volume 3, 2-6 Nov. 2004}, year={2004}, pages={2197 - 2200 Vol. 3 }, abstract={An optimum furnace charge plan model for steelmaking continuous casting planning and scheduling is presented. An improved particle swarm optimization is presented to solve the optimum charge plan problem. Simulations have been carried and the results..... } } @inproceedings{ieeebib473, title={ Tracking non-stationary optimal solution by particle swarm optimizer}, author = {X. Cui and C.T. Hardin and R.K. Ragade and T.E. Potok and A.S. Elmaghraby}, booktitle={Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2005 and First ACIS International Workshop on Self-Assembling Wireless Networks. SNPD/SAWN 2005}, notes={23-25 May 2005}, year={2005}, pages={133 - 138 }, abstract={In the real world, we have to frequently deal with searching for and tracking an optimal solution in a dynamic environment. This demands that the algorithm not only find the optimal solution but also track the trajectory of the solution in a dynamic ..... } } @inproceedings{ieeebib474, title={ Application of particle swarm optimization algorithm for weighted fuzzy rule-based system}, author = {Yijian Liu and Xuemei Zhu and Jianming Zhang and Shuqing Wang}, booktitle={Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE}, notes={Volume 3, 2-6 Nov. 2004}, year={2004}, pages={2188 - 2191 Vol. 3 }, abstract={The particle swarm optimization (PSO) algorithm is an evolutional optimization method. Some of the attractive features of the PSO algorithm include its easy implementation and the fact that no gradient information is required. In this paper, a weight..... } } @inproceedings{ieeebib475, title={ Particle swarm optimization (PSO) for reflector antenna shaping}, author = {D. Gies and Y. Rahmat-Samii}, booktitle={Antennas and Propagation Society International Symposium, 2004. IEEE}, notes={Volume 3, 20-25 June 2004}, year={2004}, pages={2289 - 2292 Vol.3 }, abstract={It has been shown that reflector antenna systems can benefit substantially from careful shaping of the main or sub-reflectors, or both, in order to maximize the antenna's performance (Duan, D.-W. and Rahmat-Samii, Y., 1995). Shaped reflectors can be ..... } } @inproceedings{ieeebib476, title={ Vector evaluated particle swarm optimization (VEPSO): optimization of a radiometer array antenna}, author = {D. Gies and Y. Rahmat-Samii}, booktitle={Antennas and Propagation Society International Symposium, 2004. IEEE}, notes={Volume 3, 20-25 June 2004}, year={2004}, pages={2297 - 2300 Vol.3 }, abstract={Particle swarm optimization (PSO) has been receiving increasing interest from the engineering design community in the last couple of years. The successful application of genetic algorithms (GA) to a wide-range of engineering design problems has provi..... } } @inproceedings{ieeebib477, title={ Particle swarm optimization of microwave microstrip filters}, author = {L. Matekovits and M. Mussetta and P. Pirinoli and S. Selleri and R.E. Zich}, booktitle={Antennas and Propagation Society International Symposium, 2004. IEEE}, notes={Volume 3, 20-25 June 2004}, year={2004}, pages={2731 - 2734 Vol.3 }, abstract={Particle swarm optimization is here applied to the design of a microwave microstrip line filter. A friction factor is introduced to slow down particles and speed up convergence, as well as a sort of "implicit restart". A comparison with genetic algor..... } } @inproceedings{ieeebib478, title={ A global search strategy of quantum-behaved particle swarm optimization}, author = {Jun Sun and Wenbo Xu and Bin Feng}, booktitle={2004 IEEE Conference on Cybernetics and Intelligent Systems}, note={Volume 1, 1-3 Dec. 2004}, year={2004}, pages={111 - 116 vol.1 }, abstract={Based on the quantum-behaved particle swarm optimization (QPSO) algorithm, we formulate the philosophy of QPSO and introduce a so-called mainstream thought of the population to evaluate the search scope of a particle and thus propose a novel paramete..... } } @inproceedings{ieeebib479, title={ An elitist distributed particle swarm algorithm for RFIC optimization}, author = {Min Chu and D.J. Allstot}, booktitle={Design Automation Conference, 2005. Proceedings of the ASP-DAC 2005. Asia and South Pacific}, notes={Volume 2, 18-21 Jan. 2005}, year={2005}, pages={671 - 674 Vol. 2 }, abstract={An RF IC optimization methodology based on an elitist distributed particle swarm optimization algorithm is presented. By including a Pareto ranking mechanism and elitism in the algorithm, design alternatives and tradeoff information are provided with..... } } @inproceedings{ieeebib48, title={ Transmission network optimal planning using the particle swarm optimization method}, author = {Ping Ren and Li-Qun Gao and Nan Li and Yang Li and Zhi-Ling Lin}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005. }, notes={Volume 7, 18-21 Aug. 2005}, year={2005}, pages={4006 - 4011 Vol. 7 }, abstract={In this paper, power system transmission network planning is formulated as a multi-objective mathematical optimization problem. In this context, three objectives: investment cost, reliability and environmental impact are considered in the optimizatio..... } } @inproceedings{ieeebib480, title={ A particle swarm optimization-least mean squares algorithm for adaptive filtering}, author = {D.J. Krusienski and W.K. Jenkins}, booktitle={Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004}, notes={Volume 1, 7-10 Nov. 2004}, year={2004}, pages={241 - 245 Vol.1 }, abstract={A particle swarm optimization-least mean squares (PSO-LMS) algorithm is presented for adapting various classes of filter structures. The LMS algorithm is widely accepted as the preeminent adaptive filtering algorithm because of its speed, efficiency ..... } } @inproceedings{ieeebib481, title={ Designing templates for cellular neural networks using particle swarm optimization}, author = {H.A. Firpi and E.D. Goodman}, booktitle={Proceedings of the 33rd Applied Imagery Pattern Recognition Workshop, 2004. }, notes={13-15 Oct. 2004}, year={2004}, pages={119 - 123 }, abstract={Designing or learning of templates for cellular neural networks constitutes one of the crucial research problems of this paradigm. In this work, we present the use of a particle swarm optimizer, a global search algorithm, to design a template set for..... } } @inproceedings{ieeebib482, title={ Using vector operations to identify niches for particle swarm optimization}, author = {I.L. Schoeman and A.P. Engelbrecht}, booktitle={2004 IEEE Conference on Cybernetics and Intelligent Systems}, note={Volume 1, 1-3 Dec. 2004}, year={2004}, pages={361 - 366 vol.1 }, abstract={In some problems described by objective functions, it is important to find all optimal solutions in the problem space. The particle swarm optimizer has originally been designed to locate a single optimum and avoid premature convergence on suboptimal ..... } } @inproceedings{ieeebib483, title={ Blending scheduling based on particle swarm optimization algorithm}, author = {Xiaoqiang Zhao and Gang Rong}, booktitle={2004. IRI 2004. Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration}, notes={8-10 Nov. 2004}, year={2004}, pages={618 - 622}, abstract={Blending is an important unit operation in process industry. Blending scheduling is nonlinear optimization problem with constraints. It is difficult to obtain optimum solution by other general optimization methods. Particle swarm optimization (PSO) a..... } } @inproceedings{ieeebib484, title={ Particle swarm optimization algorithms with novel learning strategies}, author = {J.J. Liang and A.K. Qin and P.M. Suganthan and S. Baskar}, booktitle={2004 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 4, 10-13 Oct. 2004}, year={2004}, pages={3659 - 3664 vol.4}, abstract={This paper proposes three versions of particle swarm optimizers (PSO) with novel learning strategies where each dimension of a particle learns from just one particle's historical best information, while each particle learns from different particles' ..... } } @inproceedings{ieeebib485, title={ TSK-type recurrent fuzzy network design by the hybrid of genetic algorithm and particle swarm optimization}, author = {Chia-Feng Juang and Yuan-Chang Liou}, booktitle={2004 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 3, 10-13 Oct. 2004}, year={2004}, pages={2314 - 2318 vol.3}, abstract={TSK-type recurrent fuzzy network (TRFN) design by the hybrid of genetic algorithm (GA) and particle swarm optimization (PSO), called HGAPSO, is proposed in this paper. In HGAPSO, individuals in a new generation are created, not only by crossover and ..... } } @inproceedings{ieeebib486, title={ A blind source separation algorithm using particle swarm optimization}, author = {Ying Gao and Shengli Xie}, booktitle={Proceedings of the IEEE 6th Circuits and Systems Symposium on Emerging Technologies: Frontiers of Mobile and Wireless Communication, 2004}, notes={Volume 1, 2004}, year={2004}, pages={297 - 300 Vol.1 }, abstract={In this paper, a cost function of independence of signals based on second order correlation coefficient and high order correlation coefficient is proposed, and an algorithm for linear blind source separation is presented by applying adaptive particle..... } } @inproceedings{ieeebib487, title={ Adaptive particle swarm optimization using velocity information of swarm}, author = {K. Yasuda and N. Iwasaki}, booktitle={2004 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 4, 10-13 Oct. 2004}, year={2004}, pages={3475 - 3481 vol.4}, abstract={The particle swarm optimization (PSO) method is one of the most powerful methods for solving unconstrained and constrained global optimization problems. Little is, however, known about an adaptive strategy for tuning the parameters of the PSO method ..... } } @inproceedings{ieeebib488, title={ An adaptation of particle swarm optimization for Markov decision processes}, author = {Hyeong Soo Chang}, booktitle={2004 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 2, 10-13 Oct. 2004}, year={2004}, pages={1643 - 1648 vol.2}, abstract={In this paper, we adapt the metaheuristic of particle swarm optimization (PSO) for solving nonstochastic optimization problems into a novel convergent algorithm for solving Markov decision processes (MDP) with infinite horizon discounted cost criteri..... } } @inproceedings{ieeebib489, title={ The geometric constraint solving based on memory particle swarm algorithm}, author = {Chun-Hong Cao and Wen-Hui Li and Yong-Jian Zhang and Rong-Qing Yi}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2134 - 2139 vol.4 }, abstract={Geometric constraint problem is equivalent to the problem of solving a set of nonlinear equations substantially. The constraint problem can be transformed to an optimization problem. PSO is an evolution computing method. It searches the solution spac..... } } @inproceedings{ieeebib49, title={ Automatic generating fuzzy rules with a particle swarm optimization}, author = {Ming Ma and Chun-Guang Zhou and Li-Biao Zhang and Quan-Sheng Dou}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005. }, notes={Volume 9, 18-21 Aug. 2005}, year={2005}, pages={5695 - 5698 Vol. 9 }, abstract={We have proposed a pruning algorithm to obtain the desirable fuzzy rules based on particle swarm optimization. Compared the standard particle swarm optimization, in the proposed algorithm we adopted a binary value vector and a real values vector to r..... } } @inproceedings{ieeebib490, title={ Path planning for mobile robot using the particle swarm optimization with mutation operator}, author = {Yuan-Qing Qin and De-Bao Sun and Ning Li and Yi-Gang Cen}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2473 - 2478 vol.4 }, abstract={Path planning is one of the most important technologies in the navigation of the mobile robot, which should meet the optimization and real-time requests. This paper presents a novel approach of path planning. First the MAKLINK graph is built to descr..... } } @inproceedings{ieeebib491, title={ Using relaxation velocity update strategy to improve particle swarm optimization}, author = {Yu Liu and Zheng Qin and Zeng-Lin Xu and Xing-Shi He}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2469 - 2472 vol.4 }, abstract={In particle swarm optimization (PSO), swarm intelligence is utilized when the velocities of particles are updated depending on their own experience and shared information, which is favorable for avoiding local optima. But frequently updating velociti..... } } @inproceedings{ieeebib492, title={ Modified particle swarm optimization based on space transformation for solving traveling salesman problem}, author = {Wei Pang and Kang-Ping Wang and Chun-Guang Zhou and Long-Jiang Dong and Ming Liu and Hong-Yan Zhang and Jian-Yu Wang}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2342 - 2346 vol.4 }, abstract={A modified particle swarm optimization was proposed to solve traveling salesman problem (TSP). The algorithm searched in the Cartesian continuous space, and constructed a mapping from continuous space to discrete permutation space of TSP, thus to imp..... } } @inproceedings{ieeebib493, title={ FIR filter design: frequency sampling filters by particle swarm optimization algorithm}, author = {Wan-Ping Huang and Li-Fang Zhou and Ji-Xin Qian}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2322 - 2327 vol.4 }, abstract={Based on the study of FIR filter design, a new method of designing frequency sampling filter is presented in this paper. By applying particle swarm optimization (PSO) to optimize transition sample values, the maximum stop band attenuation in FIR filt..... } } @inproceedings{ieeebib494, title={ Automatic fuzzy rule extraction based on particle swarm optimization}, author = {Ming Ma and Chun-Guang Zhou and Li-Biao Zhang and Quan-Sheng Dou}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2242 - 2245 vol.4 }, abstract={The extraction of fuzzy rules is always a difficult problem to fuzzy system. We have proposed a pruning algorithm to optimize fuzzy neural network based on particle swarm optimization algorithm. It can evolve both the fuzzy neural network's topology ..... } } @inproceedings{ieeebib495, title={ Particle swarm optimization-based texture synthesis and texture transfer}, author = {Yan Zhang and Yu Meng and Wen-Hui Li and Yun-Jie Pang and Hong-Peng Wang}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 7, 26-29 Aug. 2004}, year={2004}, pages={4037 - 4042 vol.7 }, abstract={In this paper, a fast texture synthesis algorithm-swarm intelligence-based texture synthesis is presented. The algorithm uses an intelligent particle swarm optimization (PSO) algorithm to search the best matching patch from the input sample textures ..... } } @inproceedings{ieeebib496, title={ A modified particle swarm optimization for combining forecasting}, author = {X.Y. Feng and L.M. Wan and Y.C. Liang and Y.F. Sun and H.P. Lee and Y. Wang}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2384 - 2389 vol.4 }, abstract={A modified particle swarm optimization (PSO) algorithm is proposed. Linear constraints in the PSO are added to satisfy the normalization conditions for different problems. A hybrid algorithm based on the modified PSO and combining forecasting is pres..... } } @inproceedings{ieeebib497, title={ Research on particle swarm optimization: a review}, author = {Mei-Ping Song and Guo-Chang Gu}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004}, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2236 - 2241 vol.4 }, abstract={Particle swarm optimization (PSO) explores global optimal solution through exploiting the particle's memory and the swarm's memory. Its properties of low constraint on the continuity of objective function and joint of search space, and ability of ada..... } } @inproceedings{ieeebib498, title={ Choosing a starting configuration for particle swarm optimization}, author = {M. Richards and D. Ventura}, booktitle={2004 IEEE International Joint Conference on Neural Networks, 2004. Proceedings}, notes={Volume 3, 25-29 July 2004}, year={2004}, pages={2309 - 2312 vol.3 }, abstract={The performance of particle swarm optimization can be improved by strategically selecting the starting positions of the particles. The work suggests the use of generators from centroidal Voronoi tessellations as the starting points for the swarm. The..... } } @inproceedings{ieeebib499, title={ On the hybrid of genetic algorithm and particle swarm optimization for evolving recurrent neural network}, author = {Chia-Feng Juang and Yuan-Chang Liou}, booktitle={2004 IEEE International Joint Conference on Neural Networks, 2004. Proceedings}, notes={Volume 3, 25-29 July 2004}, year={2004}, pages={2285 - 2289 vol.3 }, abstract={This work describes a new evolutionary system for evolving recurrent neural networks based on the hybrid of genetic algorithm (GA) and particle swarm optimization (PSO), called HGAPSO. In HGAPSO, individuals in a new generation are created, not only ..... } } @inproceedings{ieeebib5, title={ An improved particle swarm optimization for economic dispatch problems with non-smooth cost functions}, author = {Jong-Bae Park and Yun-Won Jeong and Woo-Nam Lee and Joong-Rin Shin}, booktitle={Power Engineering Society General Meeting, 2006. IEEE}, notes={18-22 June 2006}, year={2006}, pages={7 pp. }, abstract={This paper presents a novel and efficient method for solving the economic dispatch problems with non-smooth cost functions, by integrating the particle swarm optimization (PSO) with the chaotic sequences. The proposed improved particle swarm optimiza..... } } @inproceedings{ieeebib50, title={ A hybrid particle swarm optimization for distribution state estimation}, author = {S. Naka and T. Genji and T. Yura and Y. Fukuyama}, booktitle={Power Engineering Society General Meeting, 2003, IEEE}, notes={Volume 2, 13-17 July 2003}, year={2003}, abstract={This paper proposes a hybrid particle swarm optimization for a practical distribution state estimation. The proposed method considers nonlinear characteristics of the practical equipment and actual limited measurements in distribution systems. The me..... } } @inproceedings{ieeebib54, title={Fuzzy logic based multi-optimum programming in particle swarm optimization}, author={Lei Wang and Qi Kang and Fei Qiao and Qidi Wu}, booktitle={Proceedings of IEEE Networking, Sensing and Control, 2005}, notes={19-22 March 2005}, year={2005}, pages={473 - 477 }, abstract={It is effective to avoid falling into local optimums at the original stage of the computation that the knowledge of multi-optimum distribution state is introduced into general programming of the particle swarm movement in particle swarm optimization ..... } } @inproceedings{ieeebib500, title={ Covering Pareto-optimal fronts by subswarms in multi-objective particle swarm optimization}, author = {S. Mostaghim and J. Teich}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 2, 19-23 June 2004}, year={2004}, pages={1404 - 1411 Vol.2 }, abstract={Covering the whole set of Pareto-optimal solutions is a desired task of multiobjective optimization methods. Because in general it is not possible to determine this set, a restricted amount of solutions are typically delivered in the output to decisi..... } } @inproceedings{ieeebib501, title={ A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems}, author = {J. Vesterstrom and R. Thomsen}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 2, 19-23 June 2004}, year={2004}, pages={1980 - 1987 Vol.2 }, abstract={Several extensions to evolutionary algorithms (EAs) and particle swarm optimization (PSO) have been suggested during the last decades offering improved performance on selected benchmark problems. Recently, another search heuristic termed differential..... } } @inproceedings{ieeebib502, title={ Bi-criteria model for locating a semi-desirable facility on a plane using particle swarm optimization}, author = {H. Yapicioglu and G. Dozier and A.E. Smith}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 2, 19-23 June 2004}, year={2004}, pages={2328 - 2334 Vol.2 }, abstract={The problem of locating a semi-desirable facility on a plane is considered. A bi-criteria model is used. One of the criteria is well known minimum criterion. The second criterion is a weighted sum of Euclidean distances raised to the power of negativ..... } } @inproceedings{ieeebib503, title={ Co-evolutionary particle swarm optimization applied to the 7/spl times/7 Seega game}, author = {A.M. Abdelbar and S. Ragab and S. Mitri}, booktitle={2004 IEEE International Joint Conference on Neural Networks, 2004. Proceedings}, notes={Volume 1, 25-29 July 2004}, year={2004}, pages={ }, abstract={Seega is an ancient Egyptian two-stage board game that, in certain aspects, is more difficult than chess. The two-player game is most commonly played on a 7 /spl times/ 7 board, but is also sometimes played on a 5 /spl times/ 5 or 9 /spl times/ 9 boa..... } } @inproceedings{ieeebib504, title={ On the use of a population-based particle swarm optimizer to design combinational logic circuits}, author = {E.H. Luna and C.A. Coello Coello and A.H. Aguirre}, booktitle={2004 NASA/DoD Conference on Evolvable Hardware, 2004. Proceedings}, notes={24-26 June 2004}, year={2004}, pages={183 - 190 }, abstract={In this paper, we introduce the use of a population-based selection scheme in a particle swarm optimizer used for designing combinational logic circuits. The scheme aims to distribute the search effort in a better way within the particles of the popu..... } } @inproceedings{ieeebib505, title={ A comparative study of encodings to design combinational logic circuits using particle swarm optimization}, author = {C.A. Coello Coello and E.H. Luna and A.H. Aguirre}, booktitle={2004 NASA/DoD Conference on Evolvable Hardware, 2004. Proceedings}, notes={24-26 June 2004}, year={2004}, pages={71 - 78 }, abstract={This paper extends our original proposal to use particle swarm optimization (PSO) to design combinational logic circuits (Coello Coello et al., 2003) in which a binary representation was adopted. In this case, we study the impact of the representatio..... } } @inproceedings{ieeebib506, title={ Dynamic economic dispatch in electricity market using particle swarm optimization algorithm}, author = {Bo Zhao and Chuangxin Guo and Yijia Cao}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 6, 15-19 June 2004}, year={2004}, pages={5050 - 5054 Vol.6 }, abstract={This paper has proposed a bid-based dynamic economic dispatch model to maximize the social profit in a competitive electricity market. The model synthetically considers various constraints such as ramp rates, transmission line capacity and emission c..... } } @inproceedings{ieeebib507, title={ Particle swarm optimization based algorithm for machining parameter optimization}, author = {Liang Gao and Haibing Gao and Chi Zhou}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 4, 15-19 June 2004}, year={2004}, pages={2867 - 2871 Vol.4 }, abstract={Selection of machining parameters is an important step in process planning. In view of this problem, a new methodology based on particle swarm optimization (PSO) is developed to optimize machining conditions. First, by introducing the concept of hist..... } } @inproceedings{ieeebib508, title={ Multiuser detector based on particle swarm algorithm}, author = {Zhen-su Lu and Shi Yan}, booktitle={Proceedings of the IEEE 6th Circuits and Systems Symposium on Emerging Technologies: Frontiers of Mobile and Wireless Communication, 2004}, notes={Volume 2, 31 May-2 June 2004}, year={2004}, pages={783 - 786 Vol.2 }, abstract={Genetic algorithms (GA) have proven to be a useful method of optimization for multidimensional engineering problems. A new method named particle swarm optimization (PSO) has been proposed by Kennedy and Eberhart and it can accomplish the same goal as..... } } @inproceedings{ieeebib509, title={ Adaptive particle swarm optimization algorithm}, author = {Tao Cai and Feng Pan and Jie Chen}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 3, 15-19 June 2004}, year={2004}, pages={2245 - 2247 Vol.3 }, abstract={The particle swarm optimization (PSO) has exhibited good performance on optimization. However, the parameters, which greatly influence the algorithm stability and performance, are selected depending on experience of designer. The selection of paramet..... } } @inproceedings{ieeebib51, title={ A novel fast motion estimation method based on particle swarm optimization}, author = {Guang-Yu Du and Tian-Shu Huang and Li-Xin Song and Bing-Jie Zhao}, booktitle={Proceedings of 2005 International Conference on Machine Learning and Cybernetics, 2005. }, notes={Volume 8, 18-21 Aug. 2005}, year={2005}, pages={5038 - 5042 Vol. 8 }, abstract={Motion estimation is an important and computationally intensive task in video application. Block matching based fast algorithm reduce the computational complexity of motion estimation at the expense of accuracy. Fast motion estimation algorithms ofte..... } } @inproceedings{ieeebib510, title={ Particle Swarm Optimization method for Vehicle Routing Problem}, author = {Wu Bin and Zhao Yanwei and Ma Yaliang and Dong Hongzhao and Wang Weian}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 3, 15-19 June 2004}, year={2004}, pages={2219 - 2221 Vol.3 }, abstract={Vehicle Routing Problem is a well-known NP problem, many heuristic algorithms, such as Genetic algorithm, and Simulated Annealing algorithm is applied in the problem. The investigation of the performance of the Particle Swarm Optimization (PSO) metho..... } } @inproceedings{ieeebib511, title={ Particle Swarm Optimization for Constrained Layout Optimization}, author = {Li Ning and Liu Fei and Sun Debao and Huang Chang}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 3, 15-19 June 2004}, year={2004}, pages={2214 - 2218 Vol.3 }, abstract={Taking the layout problem of satellite cabins as the background, the authors make a study of the optimal layout problem of circle groups in a circular container with performance constraints of equilibrium and inertia, which belong to NP-Hard problem...... } } @inproceedings{ieeebib512, title={ Analysis of particle swarm optimization based on discrete time linear system theory}, author = {Ying Tan and Jianchao Zeng and Huimin Gao}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 3, 15-19 June 2004}, year={2004}, pages={2210 - 2213 Vol.3 }, abstract={Particle swarm optimization (PSO) is a new evolutionary computation method. Analysis of the evolutionary trajectories and the convergence properties of PSO are presented based on the discrete time linear system theory, and the conditions for choosing..... } } @inproceedings{ieeebib513, title={ Texture synthesis using particle swarm optimization}, author = {Yan Zhang and Yu Meng and Wenhui Li and Yunjie Pang}, booktitle={2004 International Conference on Communications, Circuits and Systems, 2004. ICCCAS 2004}, notes={Volume 2, 27-29 June 2004}, year={2004}, pages={969 - 973 Vol.2 }, abstract={In this paper, we present a survey of traditional and contemporary texture synthesis methods. It is a texture synthesis form sample. The algorithm uses a particle swarm optimization (PSO) algorithm to search the best matching patch from the input sam..... } } @inproceedings{ieeebib514, title={ A guaranteed convergence dynamic double particle swarm optimizer}, author = {Zhihua Cui and Jianchao Zeng and Xingjuan Cai}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 3, 15-19 June 2004}, year={2004}, pages={2184 - 2188 Vol.3 }, abstract={A new particle swarm optimizer (PSO), called dynamic double PSO, which is guaranteed to convergence to the global optimization solution with probability one, is presented based on the analysis of the standard PSO. Global convergence analysis is made ..... } } @inproceedings{ieeebib515, title={ Research on neural network predictive control based on particle swarm optimization}, author = {Jianmei Xiao}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 1, 15-19 June 2004}, year={2004}, pages={603 - 606 Vol.1 }, abstract={A new nonlinear predictive control algorithm is presented. The radial basis function neural network is used as multi-step predictive model. The particle swarm optimization algorithm is applied to perform the nonlinear optimization to enhance the conv..... } } @inproceedings{ieeebib516, title={ Randomized directed neighborhoods with edge migration in particle swarm optimization}, author = {A.S. Mohais and C. Ward and C. Posthoff}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={548 - 555 Vol.1 }, abstract={A key feature of particle swarm optimization algorithms is that fitness information shared with individuals in a particle's neighborhood. The kind of neighborhood structure that is used affects the rate at which information is disseminated throughout..... } } @inproceedings{ieeebib517, title={ Particle swarm optimization with adaptive linkage learning}, author = {D. Devicharan and C.K. Mohan}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={530 - 535 Vol.1 }, abstract={In many problems, the quality of solutions and computational effort required by optimization algorithms can be improved by exploiting knowledge found in the linkages or interrelations between problem dimensions or components. These linkages are somet..... } } @inproceedings{ieeebib518, title={ A hybrid swarm optimizer for efficient parameter estimation}, author = {S. Katare and A. Kalos and D. West}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={309 - 315 Vol.1 }, abstract={This paper proposes a hybrid algorithm for parameter estimation - a population-based, stochastic, particle swarm optimizer to identify promising regions of search space that are further locally explored by a Levenburg-Marquardt optimizer. This hybrid..... } } @inproceedings{ieeebib519, title={ Ocean color inversion by particle swarm optimization}, author = {W.H., Jr. Slade and H. Ressom and M.T. Musavi and R.L. Miller}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={971 - 977 Vol.1 }, abstract={Inversion of ocean color reflectance measurements can be cast as an optimization problem, where certain parameters of a forward model are optimized in order to make the forward modelled spectral reflectance match the spectral reflectance of a given i..... } } @inproceedings{ieeebib52, title={ FPGA implementation of particle swarm optimization for inversion of large neural networks}, author = {P.D. Reynolds and R.W. Duren and M.L. Trumbo and R.J., II Marks}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={389 - 392}, abstract={Particle swarm inversion of large neural networks is a computationally intensive process. By the implementing a modified particle swarm optimizer and neural network in reconfigurable hardware, many of the computations can be preformed simultaneously,..... } } @inproceedings{ieeebib520, title={ A particle swarm model for tracking multiple peaks in a dynamic environment using speciation}, author = {D. Parrott and Xiaodong Li}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={98 - 103 Vol.1 }, abstract={A particle swarm optimisation model for tracking multiple peaks in a continuously varying dynamic environment is described. To achieve this, a form of speciation allowing development of parallel subpopulations is used. The model employs a mechanism t..... } } @inproceedings{ieeebib521, title={ Autonomous agent response learning by a multi-species particle swarm optimization}, author = {Chi-kin Chow and Hung-tat Tsui}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={778 - 785 Vol.1 }, abstract={An autonomous agent response learning (AARL) algorithm is presented in this paper. We proposed to decompose the award function into a set of local award functions. By optimizing this objective function set, the response function with maximum award ca..... } } @inproceedings{ieeebib522, title={ FPGA placement and routing using particle swarm optimization}, author = {V.G. Gudise and G.K. Venayagamoorthy}, booktitle={IEEE Computer society Annual Symposium on VLSI, 2004. Proceedings}, notes={19-20 Feb. 2004}, year={2004}, pages={307 - 308 }, abstract={Field programmable gate arrays (FPGAs) are becoming increasingly important implementation platforms for digital circuits. One of the necessary requirements to effectively utilize the FPGA's fixed resources is an efficient placement and routing mechan..... } } @inproceedings{ieeebib523, title={ Co-evolutionary particle swarm optimization for min-max problems using Gaussian distribution}, author = {R.A. Krohling and F. Hoffmann and Ld.S. Coelho}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={959 - 964 Vol.1 }, abstract={Previous work presented an approach based on coevolutionary particle swarm optimization (Co-PSO) to solve constrained optimization problems formulated as min-max problems. Preliminary results demonstrated that Co-PSO constitutes a promising approach ..... } } @inproceedings{ieeebib524, title={ Vulnerability analysis of AIS-based intrusion detection systems via genetic and particle swarm red teams}, author = {G. Dozier and D. Brown and J. Hurley and K. Cain}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={111 - 116 Vol.1 }, abstract={Artificial immune systems (AISs) are biologically inspired problem solvers that have been used successfully as intrusion detection systems (IDSs). In this paper we compare a genetic hacker with 12 evolutionary hackers based on particle swarm optimiza..... } } @inproceedings{ieeebib525, title={ Recent advances in particle swarm}, author = {Xiaohui Hu and Yuhui Shi and R. Eberhart}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={90 - 97 Vol.1 }, abstract={This paper reviews the development of the particle swarm optimization method in recent years. Included are brief discussions of various parameters. Modifications to adapt to different and complex environments are reviewed, and real world applications..... } } @inproceedings{ieeebib526, title={ Optimizing semiconductor devices by self-organizing particle swarm}, author = {Xiao-Feng Xie and Wen-Jun Zhang and De-Chun Bi}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 2, 19-23 June 2004}, year={2004}, pages={2017 - 2022 Vol.2 }, abstract={A self-organizing particle swarm is presented. It works in dissipative state by employing the small inertia weight, according to experimental analysis on a simplified model, which with fast convergence. Then by recognizing and replacing inactive part..... } } @inproceedings{ieeebib527, title={ Particle swarm optimization algorithm in signal detection and blind extraction}, author = {Ying Zhao and Junli Zheng}, booktitle={7th International Symposium on Parallel Architectures, Algorithms and Networks, 2004. Proceedings}, notes={10-12 May 2004}, year={2004}, pages={37 - 41 }, abstract={The particle swarm optimization (PSO) algorithm, which originated as a simulation of a simplified social system, is an evolutionary computation technique. In this paper the binary and real-valued versions of PSO algorithm are exploited in two importa..... } } @inproceedings{ieeebib528, title={ Particle swarm optimization for security constrained economic dispatch}, author = {R.K. Pancholi and K.S. Swarup}, booktitle={Proceedings of International Conference on Intelligent Sensing and Information Processing, 2004}, notes={2004}, year={2004}, pages={7 - 12 }, abstract={This paper presents an efficient and reliable evolutionary based approach to solve the economic load dispatch (ELD) with security constraints. The proposed approach employ particle swarm optimization (PSO) algorithm for ELD. Incorporation of type 1 P..... } } @inproceedings{ieeebib529, title={ Simulation of a new hybrid particle swarm optimization algorithm}, author = {M.M. Noel and T.C. Jannett}, booktitle={Proceedings of the Thirty-Sixth Southeastern Symposium on System Theory, 2004}, notes={2004}, year={2004}, pages={150 - 153 }, abstract={In this paper a new hybrid particle swarm optimization (PSO) algorithm is introduced which makes use of gradient information to achieve faster convergence without getting trapped in local minima. Simulation results comparing the standard PSO algorith..... } } @inproceedings{ieeebib53, title={ Hybrid strategies for optimizing continuous casting process of steel}, author = {Peng Zheng and Juan Guo and Xiao-Jing Hao}, booktitle={2004. IEEE ICIT '04. 2004 IEEE International Conference on Industrial Technology}, notes={Volume 3, 8-10 Dec. 2004}, year={2004}, pages={1156 - 1161 Vol. 3}, abstract={A new hybrid evolutionary-based method combining particle swarm algorithm and chaotic search is proposed for optimizing the secondary cooling process in continuous casting of steel. This method is employed to explore the space parameter settings to m..... } } @inproceedings{ieeebib530, title={ The role of /spl epsi/-dominance in multi objective particle swarm optimization methods}, author = {S. Mostaghim and J. Teich}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 3, 8-12 Dec. 2003}, year={2003}, pages={1764 - 1771 Vol.3 }, abstract={In this paper, the influence of /spl epsi/-dominance on multi-objective particle swarm optimization (MOPSO) methods is studied. The most important role of /spl epsi/-dominance is to bound the number of non-dominated solutions stored in the archive (a..... )} } @inproceedings{ieeebib531, title={ Layout optimization of manufacturing cells using particle swarm optimization}, author = {J. Lei and Y. Yamada and Y. Komura}, booktitle={SICE 2003 Annual Conference}, notes={Volume 1, 2003}, year={2003}, pages={392 - 396 Vol.1 }, abstract={This paper proposes a 3D graphics simulation environment for the analysis and evaluation of the reconfigurable manufacturing system. The reconfigurable manufacturing system consists of mobile robots, input stations, output stations, movable manufactu..... } } @inproceedings{ieeebib532, title={ A new class of operators to accelerate particle swarm optimization}, author = {Tiew-On Ting and M.V.C. Rao and C.K. Loo and Sze-San Ngu}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 4, 8-12 Dec. 2003}, year={2003}, pages={2406 - 2410 Vol.4 }, abstract={We present some experiments with a new class of variations of mutation to accelerate the convergence of PSO. These robust mutation variations are tested on benchmark problems and the results show a significant improvement as compared to the original ..... } } @inproceedings{ieeebib533, title={ Genetic algorithm (GA) and particle swarm optimization (PSO) in engineering electromagnetics}, author = {Y. Rahmat-Samii}, booktitle={17th International Conference on Applied Electromagnetics and Communications, 2003. ICECom 2003}, notes={1-3 Oct. 2003}, year={2003}, pages={1 - 5 }, abstract={Modern antenna designers are constantly challenged to seek for optimum solutions for complex electromagnetic device designs. The temptation has grown because of ever increasing advances in computational power. The standard brute force design techniqu..... } } @inproceedings{ieeebib534, title={ Variable structure load frequency controller using particle swarm optimization technique}, author = {N.A. Al-Musabi and Z.M. Al-Hatnouz and H.N. Al-Duwaish and S. Al-Baiyat }, booktitle={2003. ICECS 2003. Proceedings of the 2003 10th IEEE International Conference on Electronics, Circuits and Systems}, notes={Volume 1, 14-17 Dec. 2003}, year={2003}, pages={380 - 383 Vol.1}, abstract={In this paper, selection of the variable structure controller feedback gains by Particle Swarm Optimization (PSO) technique is presented contrary to the trial and error selection of the variable structure feedback gains reported in literature. The pr..... } } @inproceedings{ieeebib535, title={ A first study of fuzzy cognitive maps learning using particle swarm optimization}, author = {K.E. Parsopoulos and E.I. Papageorgiou and P.P. Groumpos and M.N. Vrahatis}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 2, 8-12 Dec. 2003}, year={2003}, pages={1440 - 1447 Vol.2 }, abstract={We introduce a new algorithm for fuzzy cognitive maps learning. The proposed approach is based on the particle swarm optimization method and it is used for the detection of proper weight matrices that lead the fuzzy cognitive map to desired steady st..... } } @inproceedings{ieeebib536, title={ Comparing particle swarms for tracking extrema in dynamic environments}, author = {Xiaodong Li and Khanh Hoa Dam}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 3, 8-12 Dec. 2003}, year={2003}, pages={1772 - 1779 Vol.3 }, abstract={This work presents a comparative study of particle swarm models on their abilities to track extrema in dynamic environments. A standard PSO, two randomized PSOs, and a fine-grained PSO are evaluated in non-trivial multimodal dynamic environments invo..... } } @inproceedings{ieeebib537, title={ On the use of particle swarm optimization with multimodal functions}, author = {S.C. Esquivel and C.A.C. Coello}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 2, 8-12 Dec. 2003}, year={2003}, pages={1130 - 1136 Vol.2 }, abstract={We present two hybrid particle swarm optimization (PSO) algorithms that incorporate a mutation operator similar to the one used with evolutionary algorithms. We study our hybridized PSO algorithm with two schemes called g/spl I.bar/best and l/spl I.b..... } } @inproceedings{ieeebib538, title={ A hierarchical particle swarm optimizer}, author = {S. Janson and M. Middendorf}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 2, 8-12 Dec. 2003}, year={2003}, pages={770 - 776 Vol.2 }, abstract={A hierarchical version of the particle swarm optimization method called H-PSO is introduced. In H-PSO the particles are arranged in a dynamic hierarchy that is used to define a neighborhood structure. Depending on the quality of their so far best fou..... } } @inproceedings{ieeebib539, title={ A comparison of constraint-handling methods for the application of particle swarm optimization to constrained nonlinear optimization problems}, author = {G. Coath and S.K. Halgamuge}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 4, 8-12 Dec. 2003}, year={2003}, pages={2419 - 2425 Vol.4 }, abstract={We present a comparison of two constraint-handling methods used in the application of particle swarm optimization (PSO) to constrained nonlinear optimization problems (CNOPs). A brief review of constraint-handling techniques for evolutionary algorith..... } } @inproceedings{ieeebib540, title={ Intelligent fuzzy controller using particle swarm optimization for control of permanent magnet synchronous motor for electric vehicle}, author = {A.S. Elwer and S.A. Wahsh and M.O. Khalil and A.M. Nur-Eldeen}, booktitle={Industrial Electronics Society, 2003. IECON '03. The 29th Annual Conference of the IEEE}, notes={Volume 2, 2-6 Nov. 2003}, year={2003}, pages={1762 - 1766 Vol.2 }, abstract={Electric vehicle (EV) is a dream for the human being city traffic without exhausting gas and with low noise. Permanent magnet synchronous motor (PMSM) became at the top of ac motors in high performance drive systems such as EV. This paper presents a ..... } } @inproceedings{ieeebib541, title={ Particle swarm optimization for economic dispatch with line flow and voltage constraints [power generation scheduling]}, author = {R.K. Pancholi and K.S. Swarup}, booktitle={TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region}, notes={Volume 1, 15-17 Oct. 2003}, year={2003}, pages={450 - 455 Vol.1 }, abstract={This paper presents an efficient and reliable evolutionary based approach to solve the economic load dispatch (ELD) with lineflows and voltage constraints The proposed approach employ a particle swarm optimization (PSO) algorithm for ELD. The incorpo..... } } @inproceedings{ieeebib542, title={ Particle swarm optimization based hybrid intelligent algorithm}, author = {Qian-Lizhang and Xing Li and Quang-Anh Tran}, booktitle={2003 International Conference on Machine Learning and Cybernetics}, notes={Volume 3, 2-5 Nov. 2003}, year={2003}, pages={1648 - 1650 Vol.3 }, abstract={The hybrid intelligent algorithm is often used to solve stochastic programming problems. In this paper, we propose the particle swarm optimization (PSO) based hybrid intelligent algorithm. Preliminary experiment results suggest that this algorithm is..... } } @inproceedings{ieeebib543, title={ Particle swarm optimization for traveling salesman problem}, author = {Kang-Ping Wang and Lan Huang and Chun-Guang Zhou and Wei Pang}, booktitle={2003 International Conference on Machine Learning and Cybernetics}, notes={Volume 3, 2-5 Nov. 2003}, year={2003}, pages={1583 - 1585 Vol.3 }, abstract={This paper proposes a new application of particle swarm optimization for traveling salesman problem. We have developed some special methods for solving TSP using PSO. We have also proposed the concept of swap operator and swap sequence, and redefined..... } } @inproceedings{ieeebib544, title={ Layout optimization of manufacturing cells and allocation optimization of transport robots in reconfigurable manufacturing systems using particle swarm optimization}, author = {Y. Yamada and K. Ookoudo and Y. Komura}, booktitle={2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings}, notes={Volume 2, 27-31 Oct. 2003}, year={2003}, pages={2049 - 2054 vol.2 }, abstract={This paper proposes a 3D graphics simulation environment for the analysis and evaluation of reconfigurable manufacturing systems. The reconfigurable manufacturing systems consist of transport robots; input stations, output stations, movable manufactu..... } } @inproceedings{ieeebib545, title={ Adaptive particle swarm optimization}, author = {K. Yasuda and A. Ide and N. Iwasaki}, booktitle={2003. IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 2, 5-8 Oct. 2003}, year={2003}, pages={1554 - 1559 vol.2}, abstract={The particle swarm optimization (PSO) method is one of the most powerful methods for solving unconstrained and constrained global optimization problems. Little is, however, known about how the PSO method works or finds a globally optimal solution of ..... } } @inproceedings{ieeebib546, title={ Inversion of neural network underwater acoustic model for estimation of bottom parameters using modified particle swarm optimizers}, author = {B.B. Thompson and R.J., II Marks and M.A. El-Sharkawi and W.J. Fox and R.T. Miyamoto}, booktitle={Proceedings of the International Joint Conference on Neural Networks, 2003}, notes={Volume 2, 20-24 July 2003}, year={2003}, pages={1301 - 1306 vol.2 }, abstract={Given a complicated and computationally intensive underwater acoustic model in which some acoustic measurement is a function of sonar system and environmental parameters, it is computationally beneficial to train a neural network to emulate the prope..... } } @inproceedings{ieeebib547, title={ Evolving digital circuits using particle swarm}, author = {V.G. Gudise and G.K. Venayagamoorthy}, booktitle={Proceedings of the International Joint Conference on Neural Networks, 2003}, notes={Volume 1, 20-24 July 2003}, year={2003}, pages={468 - 472 vol.1 }, abstract={Particle swarm optimization (PSO) motivated by the social behavior of organisms is proposed for evolution of combinational logic circuits. Results are presented to show that PSO based evolution of digital circuits are equivalent to or even with bette..... } } @inproceedings{ieeebib548, title={ Reconfigurable array design using parallel particle swarm optimization}, author = {D. Gies and Y. Rahmat-Samii}, booktitle={Antennas and Propagation Society International Symposium, 2003. IEEE}, notes={Volume 1, 22-27 June 2003}, year={2003}, pages={177 - 180 vol.1 }, abstract={Reconfigurable antenna arrays that are capable of radiating with multiple power patterns using a single power divider network are desirable for many applications. We use the particle swarm optimization (PSO) algorithm to perform dual-beam array optim..... } } @inproceedings{ieeebib549, title={ Gene clustering using self-organizing maps and particle swarm optimization}, author = {Xiang Xiao and E.R. Dow and R. Eberhart and Z.B. Miled and R.J. Oppelt}, booktitle={Proceedings of the International Parallel and Distributed Processing Symposium, 2003}, notes={22-26 April 2003}, year={2003}, pages={10 pp. }, abstract={Gene clustering, the process of grouping related genes in the same cluster, is at the foundation of different genomic studies that aim at analyzing the function of genes. Microarray technologies have made it possible to measure gene expression levels..... } } @inproceedings{ieeebib55, title={ Identification of time-varying delay systems using particle swarm optimization}, author = {Jing Ke and Yizheng Qiao and Jixin Qian}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 1, 15-19 June 2004}, year={2004}, pages={330 - 334 Vol.1 }, abstract={Particle swarm optimization algorithm is a new evolutionary computation method, which is applicable to complex optimization problems that are nonlinear, nondifferentiable and multimodal. A method for identification of time-varying delay systems using..... } } @inproceedings{ieeebib550, title={ Swarm optimisation as a new tool for data mining}, author = {T. Sousa and A. Neves and A. Silva}, booktitle={Proceedings of the International Parallel and Distributed Processing Symposium, 2003. }, notes={22-26 April 2003}, year={2003}, pages={6 pp. }, abstract={This paper proposes the use of particle swarm optimisers as a tool for data mining. To evaluate its usefulness, we empirically compare the performance of three variants of the particle optimiser with another evolutionary algorithm, namely a genetic a..... } } @inproceedings{ieeebib551, title={ Stator fault estimation in induction motors using particle swarm optimization}, author = {H.M. Emara and M.E. Ammar and A. Bahgat and H.T. Dorrah}, booktitle={ IEEE International Conference on Electric Machines and Drives Conference, 2003. IEMDC'03.}, notes={Volume 3, 1-4 June 2003}, year={2003}, pages={1469 - 1475 vol.3 }, abstract={The use of induction motors is extensive in industry. The working conditions of these motors make them subject to many faults. These faults must be detected in an early stage before they lead to catastrophic failures. This paper presents a scheme for..... } } @inproceedings{ieeebib552, title={ Utilizing particle swarm optimization to label a structured beam matrix}, author = {Qin Sun and Yuhui Shi and R.C. Eberhart and W.A. Bauson}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={118 - 123}, abstract={The use of structured lighting is common in machine vision systems where three-dimensional measurements must be made. In one method, a matrix of bright spots is projected onto an object. The spots move from predetermined positions depending on the di..... } } @inproceedings{ieeebib553, title={ Social programming using functional swarm optimization}, author = {M.S. Voss}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={103 - 109}, abstract={The development of mathematical neural networks was based on an analogy with biological neural networks found in nature. Recently there has been a resurgence in research and understanding in self-organizing networks that are based on other metaphors:..... } } @inproceedings{ieeebib554, title={ Optimal operational planning for cogeneration system using particle swarm optimization}, author = {T. Tsukada and T. Tamura and S. Kitagawa and Y. Fukuyama}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={138 - 143}, abstract={This paper proposes optimal operational planning for a cogeneration system (CGS) using particle swarm optimization (PSO). CGS is usually connected to various facilities such as refrigerators, reservoirs, and cooling towers. In order to generate optim..... } } @inproceedings{ieeebib555, title={ Particle swarm optimization recommender system}, author = {S. Ujjin and P.J. Bentley}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={124 - 131}, abstract={Recommender systems are new types of Internet-based software tools, designed to help users find their way through today's complex on-line shops and entertainment Web sites. This paper describes a new recommender system, which employs a particle swarm..... } } @inproceedings{ieeebib556, title={ Comparison of particle swarm optimization and backpropagation as training algorithms for neural networks}, author = {V.G. Gudise and G.K. Venayagamoorthy}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={110 - 117}, abstract={Particle swarm optimization (PSO) motivated by the social behavior of organisms, is a step up to existing evolutionary algorithms for optimization of continuous nonlinear functions. Backpropagation (BP) is generally used for neural network training. ..... } } @inproceedings{ieeebib557, title={ Particle swarm with extended memory for multiobjective optimization}, author = {Xiaohui Hu and R.C. Eberhart and Yuhui Shi}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={193 - 197}, abstract={This paper presents a modified dynamic neighborhood particle swarm optimization (DNPSO) algorithm for multiobjective optimization problems. PSO is modified by using a dynamic neighborhood strategy, new particle memory updating, and one-dimension opti..... } } @inproceedings{ieeebib558, title={ PSOt - a particle swarm optimization toolbox for use with Matlab}, author = {B. Birge}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={182 - 186}, abstract={A particle swarm optimization toolbox (PSOt) for use with the Matlab scientific programming environment has been developed. PSO is introduced briefly and then the use of the toolbox is explained with some examples. A link to downloadable code is prov..... } } @inproceedings{ieeebib559, title={ Fitness-distance-ratio based particle swarm optimization}, author = {T. Peram and K. Veeramachaneni and C.K. Mohan}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={174 - 181}, abstract={This paper presents a modification of the particle swarm optimization algorithm (PSO) intended to combat the problem of premature convergence observed in many applications of PSO. The proposed new algorithm moves particles towards nearby particles of..... } } @inproceedings{ieeebib56, title={ An improved particle swarm optimization algorithm with neighborhoods topologies}, author = {Wei Jian and Yun-Can Xue and Ji-Xin Qian}, booktitle={Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004. }, notes={Volume 4, 26-29 Aug. 2004}, year={2004}, pages={2332 - 2337 vol.4 }, abstract={The impacts of neighborhoods topologies on particle swarm optimization for complex functions are discussed. The suitability of three topologies to the kind of functions is experimented. The convergence features affected by constant parameters on part..... } } @inproceedings{ieeebib560, title={ Virtual instrument parameter calibration with particle swarm optimization}, author = {Peng Yu and Peng Xiyuan and Meng Shengwei}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={42 - 45}, abstract={In virtual instrument designs and applications, lots of functional parameters can be set through software methods. Currently, most parameter settings methods are lightly linked with the knowledge of instruments and basic principles related to specifi..... } } @inproceedings{ieeebib561, title={ Computing periodic orbits of nondifferentiable/discontinuous mappings through particle swarm optimization}, author = {K.E. Parsopoulos and M.N. Vrahatis}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={34 - 41}, abstract={Periodic orbits of nonlinear mappings play a central role in the study of dynamical systems. Traditional root finding algorithms, such as the Newton-family algorithms, have been widely applied for the detection of periodic orbits. However, in the cas..... } } @inproceedings{ieeebib562, title={ Engineering optimization with particle swarm}, author = {Xiaohui Hu and R.C. Eberhart and Yuhui Shi}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={53 - 57}, abstract={The paper presents a modified particle swarm optimization (PSO) algorithm for engineering optimization problems with constraints. PSO is started with a group of feasible solutions and a feasibility function is used to check if the newly explored solu..... } } @inproceedings{ieeebib563, title={ Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO)}, author = {S. Mostaghim and J. Teich}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={26 - 33}, abstract={In multi-objective particle swarm optimization (MOPSO) methods, selecting the best local guide (the global best particle) for each particle of the population from a set of Pareto-optimal solutions has a great impact on the convergence and diversity o..... } } @inproceedings{ieeebib564, title={ Adaptive particle swarm optimization on individual level}, author = {Xiao-Feng Xie and Wen-Jun Zhang and Zhi-Lian Yang}, booktitle={2002 6th International Conference on Signal Processing}, notes={Volume 2, 26-30 Aug. 2002}, year={2002}, pages={1215 - 1218 vol.2 }, abstract={An adaptive particle swarm optimization (PSO) on individual level is presented. By analyzing the social model of PSO, a replacement criterion, based on the diversity of fitness between the current particle and the best historical experience, is intro..... } } @inproceedings{ieeebib565, title={ Cluster-head identification in ad hoc sensor networks using particle swarm optimization}, author = {J. Tillett and R. Rao and F. Sahin}, booktitle={2002 IEEE International Conference on Personal Wireless Communications}, notes={15-17 Dec. 2002}, year={2002}, pages={201 - 205}, abstract={We propose a new application of the optimization technique known as particle swarm optimization (PSO) to the problem of clustering nodes. The PSO approach is an evolutionary programming technique where a 'swarm' of test solutions, analogous to a natu..... } } @inproceedings{ieeebib566, title={ Particle swarm optimization for fuzzy membership functions optimization}, author = {A.A.A. Esmin and A.R. Aoki and G. Lambert-Torres}, booktitle={2002 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 3, 6-9 Oct. 2002}, year={2002}, pages={6 pp. vol.3}, abstract={The use of fuzzy logic to solve control problems have been increasing considerably in the past years. The successfulness of fuzzy application depends on a number of parameters, such as fuzzy membership functions, that are usually decided upon subject..... } } @inproceedings{ieeebib567, title={ Solving systems of unconstrained equations using particle swarm optimization}, author = {R. Brits and A.P. Engelbrecht and F. van den Bergh}, booktitle={2002 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 3, 6-9 Oct. 2002}, year={2002}, pages={6 pp. vol.3}, abstract={A new particle swarm optimization algorithm (PSO), nbest, is developed in this paper to solve systems of unconstrained equations. For this purpose, the standard gbest PSO is adapted by redefining the fitness function in order to locate multiple solut..... } } @inproceedings{ieeebib568, title={ A new locally convergent particle swarm optimiser}, author = {F. van den Berghand A.P. Engelbrecht}, booktitle={2002 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 3, 6-9 Oct. 2002}, year={2002}, pages={6 pp. vol.3}, abstract={This paper introduces a new Particle Swarm Optimisation (PSO) algorithm with strong local convergence properties. The new algorithm performs much better with a smaller number of particles, compared to the original PSO. This property is desirable when..... } } @inproceedings{ieeebib569, title={ Tracking changing extrema with adaptive particle swarm optimizer}, author = {A. Carlisle and G. Dozler}, booktitle={World Automation Congress, 2002. Proceedings of the 5th Biannual}, notes={Volume 13, 9-13 June 2002}, year={2002}, pages={265 - 270 }, abstract={A modification of the particle swarm optimizer (PSO) involving updating obsolete particle memories has been shown to be effective in locating a changing extrema. In this paper we investigate the effectiveness of the modified PSO in tracking changing ..... } } @inproceedings{ieeebib57, title={ Particle swarm optimization based nonlinear observer}, author = {Jing Ke and Qiqiang Li and Jixin Qian}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 2, 15-19 June 2004}, year={2004}, pages={1580 - 1583 Vol.2 }, abstract={Particle swarm optimization algorithm is a new and efficient evolutionary computation method. A particle swarm optimization based nonlinear observer design method is proposed. It belongs to moving horizon estimation method. The basic idea of the meth..... } } @inproceedings{ieeebib570, title={ MOPSO: a proposal for multiple objective particle swarm optimization}, author = {C.A. Coello Coello and M.S. Lechuga}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1051 - 1056 }, abstract={This paper introduces a proposal to extend the heuristic called "particle swarm optimization" (PSO) to deal with multiobjective optimization problems. Our approach uses the concept of Pareto dominance to determine the flight direction of a particle a..... } } @inproceedings{ieeebib571, title={ Division of labor in particle swarm optimisation}, author = {J.S. Vesterstrom and J. Riget and T. Krink}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1570 - 1575 }, abstract={We introduce Division of Labor (DoL) from social insects to improve local optimisation of the Particle Swarm Optimiser (PSO). We compared the performance with the basic PSO, a GA and simulated annealing and found improvements around local optima. The..... } } @inproceedings{ieeebib572, title={ Improvised music with swarms}, author = {T.M. Blackwell and P. Bentley}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1462 - 1467 }, abstract={This paper describes SWARMUSIC, an interactive music improviser. A particle swarm algorithm generates musical material by a mapping of particle positions onto events in MIDI space. Interaction with an external musical source arises through the attrac..... } } @inproceedings{ieeebib573, title={ Dissipative particle swarm optimization}, author = {Xiao-Feng Xie and Wen-Jun Zhang and Zhi-Lian Yang}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1456 - 1461 }, abstract={A dissipative particle swarm optimization is developed according to the self-organization of dissipative structure. The negative entropy is introduced to construct an opening dissipative system that is far-from-equilibrium so as to driving the irreve..... } } @inproceedings{ieeebib574, title={ Particle swarm, genetic algorithm, and their hybrids: optimization of a profiled corrugated horn antenna}, author = {J. Robinson and S. Sinton and Y. Rahmat-Samii}, booktitle={Antennas and Propagation Society International Symposium, 2002. IEEE}, notes={Volume 1, 16-21 June 2002}, year={2002}, pages={314 - 317 vol.1 }, abstract={Genetic algorithms (GA) have proven to be a useful method of optimization for difficult and discontinuous multidimensional engineering problems. A new method of optimization, particle swarm optimization (PSO), is able to accomplish the same goal as G..... } } @inproceedings{ieeebib575, title={ Particle swarm optimizer for constrained economic dispatch with prohibited operating zones}, author = {A. El-Gallad and M. El-Hawary and A. Sallam and A. Kalas}, booktitle={Canadian Conference on Electrical and Computer Engineering, 2002. IEEE CCECE 2002}, notes={Volume 1, 12-15 May 2002}, year={2002}, pages={78 - 81 vol.1 }, abstract={Practically, not all the operating zones of generation units are available always for load allocation due to some physical operation limitations. Accordingly, these prohibited zones divide the operating region between the minimum and the maximum gene..... } } @inproceedings{ieeebib576, title={ Particle swarms for feedforward neural network training}, author = {R. Mendes and P. Cortez and M. Rocha and J. Neves}, booktitle={Proceedings of the 2002 International Joint Conference on Neural Networks, 2002. IJCNN '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1895 - 1899 }, abstract={Particle swarm is an optimization paradigm for real-valued functions, based on the social dynamics of group interaction. We propose its application to the training of neural networks. Comparative tests were carried out, for classification and regress..... } } @inproceedings{ieeebib577, title={ Extending particle swarm optimisers with self-organized criticality}, author = {M. Lovbjerg and T. Krink}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1588 - 1593 }, abstract={Particle swarm optimisers (PSOs) show potential in function optimisation, but still have room for improvement. Self-organized criticality (SOC) can help control the PSO and add diversity. Extending the PSO with SOC seems promising reaching faster con..... } } @inproceedings{ieeebib578, title={ Particle swarm optimization for integer programming}, author = {E.C. Laskari and K.E. Parsopoulos and M.N. Vrahatis}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1582 - 1587 }, abstract={The investigation of the performance of the particle swarm optimization (PSO) method in integer programming problems, is the main theme of the present paper. Three variants of PSO are compared with the widely used branch and bound technique, on sever..... } } @inproceedings{ieeebib579, title={ Particle swarm optimization for minimax problems}, author = {E.C. Laskari and K.E. Parsopoulos and M.N. Vrahatis}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1576 - 1581 }, abstract={This paper investigates the ability of the Particle Swarm Optimization (PSO) method to cope with minimax problems through experiments on well-known test functions. Experimental results indicate that PSO tackles minimax problems effectively. Moreover,..... } } @inproceedings{ieeebib58, title={ A modified particle swarm optimization algorithm}, author = {Junjun Li and Xihuai Wang}, booktitle={Fifth World Congress on Intelligent Control and Automation, 2004. WCICA 2004}, notes={Volume 1, 15-19 June 2004}, year={2004}, pages={354 - 356 Vol.1 }, abstract={A modified particle swarm optimization (PSO) algorithms is proposed. This method integrates the particle swarm optimization with the simulated annealing algorithm. It can solve the problem of local minimum of the particle swarm optimization, and narr..... } } @inproceedings{ieeebib580, title={ Don't push me! Collision-avoiding swarms}, author = {T.M. Blackwell and P. Bentley}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1691 - 1696 }, abstract={This paper examines a particle swarm algorithm which has been applied to the generation of interactive, improvised music. An important feature of this algorithm is a balance between particle attraction to the centre of mass and repulsive, collision a..... } } @inproceedings{ieeebib581, title={ Solving numerical equations of hydraulic problems using particle swarm optimization}, author = {R.A. Krohling and H. Knidel and Y. Shi}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1688 - 1690 }, abstract={This paper describes how to solve numerical equations of hydraulic problems that involve the calculation of free and forced channels. The problem is modeled by using the Manning equation. This equation allows the calculation of outflows, inclination ..... } } @inproceedings{ieeebib582, title={ Multiobjective optimization using dynamic neighborhood particle swarm optimization}, author = {Xiaohui Hu and R. Eberhart}, booktitle={Proceedings of the 2002 Congress on Evolutionary Computation, 2002. CEC '02}, notes={Volume 2, 12-17 May 2002}, year={2002}, pages={1677 - 1681 }, abstract={This paper presents a particle swarm optimization (PSO) algorithm for multiobjective optimization problems. PSO is modified by using a dynamic neighborhood strategy, new particle memory updating, and one-dimension optimization to deal with multiple o..... } } @inproceedings{ieeebib583, title={ Swarm-intelligently trained neural network for power transformer protection}, author = {A.I. El-Gallas and M. El-Hawary and A.A. Sallam and A. Kalas}, booktitle={Canadian Conference on Electrical and Computer Engineering, 2001}, notes={Volume 1, 13-16 May 2001}, year={2001}, pages={265 - 269 vol.1 }, abstract={The paper presents the particle swarm optimization technique (PSO) to train multi layer neural network for discrimination between magnetizing inrush current and internal fault current in power transformers. The discrimination process relies on the ha..... } } @inproceedings{ieeebib584, title={ A particle swarm optimization for reactive power and voltage control in electric power systems}, author = {Y. Fukuyama and H. Yoshida}, booktitle={Proceedings of the 2001 Congress on Evolutionary Computation, 2001}, notes={Volume 1, 27-30 May 2001}, year={2001}, pages={87 - 93 vol. 1 }, abstract={This paper presents a particle swarm optimization (PSO) for reactive power and voltage control (RPVC) in electric power systems. RPVC can be formulated as a mixed-integer nonlinear optimization problem (MINLP). The proposed method expands the origina..... } } @inproceedings{ieeebib585, title={ Stereotyping: improving particle swarm performance with cluster analysis}, author = {J. Kennedy}, booktitle={Proceedings of the 2000 Congress on Evolutionary Computation, 2000}, notes={Volume 2, 16-19 July 2000}, year={2000}, pages={1507 - 1512 vol.2 }, abstract={Individuals in the particle swarm population were stereotyped by cluster analysis of their previous best positions. The cluster centers then were substituted for the individuals' and neighbors' best previous positions in the algorithm. ..... } } @inproceedings{ieeebib586, title={ Comparing inertia weights and constriction factors in particle swarm optimization}, author = {R.C. Eberhart and Y. Shi}, booktitle={Proceedings of the 2000 Congress on Evolutionary Computation, 2000}, notes={Volume 1, 16-19 July 2000}, year={2000}, pages={84 - 88 vol.1 }, abstract={The performance of particle swarm optimization using an inertia weight is compared with performance using a constriction factor. Five benchmark functions are used for the comparison. It is concluded that the best approach is to use the constriction f..... } } @inproceedings{ieeebib587, title={ A particle swarm optimization for reactive power and voltage control in electric power systems considering voltage security assessment}, author = {H. Yoshida and Y. Fukuyama and S. Takayama and Y. Nakanishi}, booktitle={Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics SMC 1999}, notes={Volume 6, 12-15 Oct. 1999}, year={1999}, pages={497 - 502 vol.6}, abstract={This paper presents a particle swarm optimization (PSO) for reactive power and voltage control (Volt/Var Control: VVC) considering voltage security assessment (VSA). VVC can be formulated as a mixed-integer nonlinear optimization problem (MINLP). The..... } } @inproceedings{ieeebib588, title={ Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance}, author = {J. Kennedy}, booktitle={Proceedings of the 1999 Congress on Evolutionary Computation, 1999. CEC 99}, notes={Volume 3, 6-9 July 1999}, year={1999}, pages={ }, abstract={The study manipulated the neighborhood topologies of particle swarms optimizing four test functions. Several social network structures were tested, with small-world randomization of a specified number of links. Sociometric structure and..... } } @inproceedings{ieeebib589, title={ Particle swarm optimization: surfing the waves}, author = {E. Ozcan and C.K. Mohan}, booktitle={Proceedings of the 1999 Congress on Evolutionary Computation, 1999. CEC 99}, notes={Volume 3, 6-9 July 1999}, year={1999}, pages={ }, abstract={A new optimization method has been proposed by J. Kennedy and R.C. Eberhart (1997; 1995), called Particle Swarm Optimization (PSO). This approach combines social psychology principles and evolutionary computation. It has been applied successfully to ..... } } @inproceedings{ieeebib59, title={ Particle swarm optimization for adaptive IIR filter structures}, author = {D.J. Krusienski and W.K. Jenkins}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={965 - 970 Vol.1 }, abstract={This paper introduces the application of particle swarm optimization techniques to infinite impulse response (IIR) adaptive filter structures. Particle swarm optimization (PSO) is similar to the genetic algorithm (GA) in that it performs a structured..... } } @inproceedings{ieeebib590, title={ Extracting rules from fuzzy neural network by particle swarm optimisation}, author = {He Zhenya and Wei Chengjian and Yang Luxi and Gao Xiqi and Yao Susu and R.C. Eberhart and Yuhui Shi}, booktitle={The 1998 IEEE International Conference on Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence.}, notes={4-9 May 1998}, year={1998}, pages={74 - 77}, abstract={A four layer fuzzy neural network is presented to realise knowledge acquisition from input-output samples. The network parameters including the necessary membership functions of the input variables and the consequent parameters are tuned and identifi..... } } @inproceedings{ieeebib591, title={ Matching algorithms to problems: an experimental test of the particle swarm and some genetic algorithms on the multimodal problem generator}, author = {J. Kennedy and W.M. Spears}, booktitle={The 1998 IEEE International Conference on Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence.}, notes={4-9 May 1998}, year={1998}, pages={78 - 83}, abstract={A multimodal problem generator was used to test three versions of a genetic algorithm and the binary particle swarm algorithm in a factorial time-series experiment. Specific strengths and weaknesses of the various algorithms were identified..... } } @inproceedings{ieeebib592, title={ Using the particle swarm optimization technique to train a recurrent neural model}, author = {J. Salerno}, booktitle={Proceedings of the Ninth IEEE International Conference on Tools with Artificial Intelligence, 1997}, notes={3-8 Nov. 1997}, year={1997}, pages={45 - 49}, abstract={We discuss the results of implementing an evolutionary learning technique entitled particle swarm optimization as described by Kennedy and Eberhart (1995). We present a number of results using this technique on a number of neural model architectures ..... } } @article{ieeebibJ593, title={ Genetical Swarm Optimization: Self-Adaptive Hybrid Evolutionary Algorithm for Electromagnetics}, author={Francesco Grimaccia and Marco Mussetta and Riccardo E. Zich}, journal={IEEE Transactions on Antennas and Propagation}, volume= 55, issue= 3, date={}, part1={ March 2007 Page(s):781 - 785 }, year=2007, abstract={A new effective optimization algorithm suitably developed for electromagnetic applications called genetical swarm optimization (GSO) is presented. This is a hybrid algorithm developed in order to combine in the most effective way the properties of tw..... } } @inproceedings{ieeebib594, title={ Design of a Prefractal Monopolar Antenna for 3.4ýý3.6 GHz Wi-Max Band Portable Devices}, author = {R. Azaro and G. Boato and M. Donelli and A. Massa and E. Zeni}, booktitle={Antennas and Wireless Propagation Letters}, notes={Volume 5, Issue 1, Dec. 2006}, year={2006}, pages={116 - 119 }, abstract={In this letter, the design of a miniaturized monopolar prefractal antenna for the 3.4-3.6 GHz WiMax band is presented. The geometrical configuration of the monopolar antenna, printed on a planar dielectric substrate, has been synthesized by means of ..... } } @article{ieeebibJ595, title={ Parameter Estimation in Stochastic Mammogram Model by Heuristic Optimization Techniques}, author={S.E. Selvan and C.C. Xavier and N. Karssemeijer and J. Sequeira and R.A. Cherian and B.Y. Dhala}, journal={IEEE Transactions on Information Technology in Biomedicine}, volume= 10, issue= 4, date={ Oct. 2006}, pages={685 - 695 }, year={2006}, abstract={The appearance of disproportionately large amounts of high-density breast parenchyma in mammograms has been found to be a strong indicator of the risk of developing breast cancer. Hence, the breast density model is popular for risk estimation or for ..... } } @article{ieeebibJ596, title={ Virtual MIMO-based cross-layer design for wireless sensor networks}, author={Yong Yuan and Zhihai He and Min Chen}, journal={IEEE Transactions on Vehicular Technology}, volume= 55, issue= 3, date={ May 2006}, pages={856 - 864 }, year={2006}, abstract={In this paper, a novel multihop virtual multiple-input-multiple-output (MIMO) communication protocol is proposed by the cross-layer design to jointly improve the energy efficiency, reliability, and end-to-end (ETE) QoS provisioning in wireless sensor..... } } @article{ieeebibJ597, title={ Reserve Constrained Dynamic Dispatch of Units With Valve-Point Effects}, author={T.A.A. Victoire and A.E. Jeyakumar}, journal={IEEE Transactions on Power Systems}, volume= 20, issue= 3, date={ Aug. 2005}, pages={1273 - 1282 }, year={2005}, abstract={This paper addresses a hybrid solution methodology integrating particle swarm optimization (PSO) algorithm with the sequential quadratic programming (SQP) method for the reserve constrained dynamic economic dispatch problem (RCDEDP) of generating uni..... } } @article{ieeebibJ598, title={ Application and comparison of metaheuristic techniques to generation expansion planning problem}, author={S. Kannan and S.M.R. Slochanal and N.P. Padhy}, journal={IEEE Transactions on Power Systems}, volume= 20, issue= 1, date={ Feb 2005}, pages={466 - 475 }, year={2005}, abstract={This work presents both application and comparison of the metaheuristic techniques to generation expansion planning (GEP) problem. The Metaheuristic techniques such as the genetic algorithm, differential evolution, evolutionary programming, evolution..... } } @article{ieeebibJ599, title={ Optimal design of power-system stabilizers using particle swarm optimization}, author={M.A. Abido}, journal={IEEE Transactions on Energy Conversion}, volume= 17, issue= 3, date={ Sept. 2002}, pages={406 - 413 }, year={2002}, abstract={In this paper, a novel evolutionary algorithm-based approach to optimal design of multimachine power-system stabilizers (PSSs) is proposed. The proposed approach employs a particle-swarm-optimization (PSO) technique to search for optimal settings of ..... } } @inproceedings{ieeebib6, title={ Evolving combinational logic circuits using a hybrid quantum evolution and particle swarm inspired algorithm}, author = {P. Moore and G.K. Venayagamoorthy}, booktitle={2005 NASA/DoD Conference on Evolvable Hardware, 2005. Proceedings}, notes={29 June-1 July 2005}, year={2005}, pages={97 - 102 }, abstract={In this paper, an algorithm inspired from quantum evolution and particle swarm to evolve combinational logic circuits is presented. This algorithm uses the framework of the local version of particle swarm optimization with quantum evolutionary algori..... } } @inproceedings{ieeebib60, title={ A new stochastic particle swarm optimizer}, author = {Cui Zhihua and Zeng Jianchao and Cai Xingjuan}, booktitle={Congress on Evolutionary Computation, 2004. CEC2004}, notes={Volume 1, 19-23 June 2004}, year={2004}, pages={316 - 319 Vol.1 }, abstract={Particle swarm optimizer is a novel algorithm where a population of candidate problem solution vectors evolves "social" norms by being influenced by their topological neighbors. The standard particle swarm optimizer (PSO) may prematurely converge on ..... } } @article{ieeebibJ600, title={ Temperature control by chip-implemented adaptive recurrent fuzzy controller designed by evolutionary algorithm}, author={Chia-Feng Juang and Chao-Hsin Hsu}, journal={IEEE Transactions on [see also Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on] Circuits and Systems I: Regular Papers}, volume= 52, issue= 11, date={ Nov. 2005}, pages={2376 - 2384 }, year={2005}, abstract={Online adaptive temperature control by field-programmable gate array (FPGA) - implemented adaptive recurrent fuzzy controller (ARFC) chip is proposed in this paper. The RFC is realized according to the structure of Takagi-Sugeno-Kang (TSK)-type recur..... } } @article{ieeebibJ601, title={ Parasitic-aware RF circuit design and optimization}, author={Jinho Park and Kiyong Choi and D.J. Allstot}, journal={IEEE Transactions on [see also Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on] Circuits and Systems I: Regular Papers}, volume= 51, issue= 10, date={ Oct. 2004}, pages={1953 - 1966 }, year={2004}, abstract={RF circuit synthesis techniques based on particle swarm optimization and adaptive simulated annealing with tunneling are described, and comparisons of parasitic-aware designs of an RF distributed amplifier and a nonlinear power amplifier are presente..... } } @article{ieeebibJ602, title={ Learning to play games using a PSO-based competitive learning approach}, author={L. Messerschmidt and A.P. Engelbrecht}, journal={IEEE Transactions on Evolutionary Computation}, volume= 8, issue= 3, date={ June 2004}, pages={280 - 288 }, year={2004}, abstract={A new competitive approach is developed for learning agents to play two-agent games. This approach uses particle swarm optimizers (PSO) to train neural networks to predict the desirability of states in the leaf nodes of a game tree. The new approach ..... } } @article{ieeebibJ603, title={ The fully informed particle swarm: simpler, maybe better}, author={R. Mendes and J. Kennedy and J. Neves}, journal={IEEE Transactions on Evolutionary Computation}, volume= 8, issue= 3, date={ June 2004}, pages={204 - 210 }, year={2004}, abstract={The canonical particle swarm algorithm is a new approach to optimization, drawing inspiration from group behavior and the establishment of social norms. It is gaining popularity, especially because of the speed of convergence and the fact that it is ..... } } @article{ieeebibJ604, title={ An adaptive multimodal biometric management algorithm}, author={K. Veeramachaneni and L.A. Osadciw and P.K. Varshney}, journal={IEEE Transactions on Systems, Man and Cybernetics, Part C}, volume= 35, issue= 3, date={ Aug. 2005}, pages={344 - 356 }, year={2005}, abstract={This paper presents an evolutionary approach to the sensor management of a biometric security system that improves robustness. Multiple biometrics are fused at the decision level to support a system that can meet more challenging and varying accuracy..... } } @article{ieeebibJ605, title={ Optimized rule-based delay proportion adjustment for proportional differentiated services}, author = {S. Patchararungruang and S.K. Halgamuge and N. Shenoy}, journal={IEEE Journal on Selected Areas in Communications}, notes={Volume 23, Issue 2, Feb 2005}, year={2005}, pages={261 - 276 }, abstract={We present a novel method to adjust output queue delay proportion fairly among traffic classes of different priorities in relative differentiated services. The delay proportion adjustment is based on acceleration of incoming traffic in each class. It..... } } @inproceedings{ieeebib606, title={ Dynamic body posture tracking using evolutionary optimisation}, author = {C. Robertson and E. Trucco and S. Ivekovic}, booktitle={Electronics Letters}, notes={Volume 41, Issue 25, 8 Dec. 2005}, year={2005}, pages={1370 - 1371 }, abstract={A novel evolutionary approach for fitting and tracking articulated skeletons to 3D data of upper-body sequences typical of videoconferencing or newscasting is presented. A 24-dimensional skeleton fitting problem is solved with a novel particle swarm .....} } @inproceedings{ieeebib607, title={ Induction Machine Fault Identification using Particle Swarm Algorithms}, author = {S. A. Ethny and P. P Acarnley and B. Zahawi and D. Giaouris}, booktitle={2006 International Conference on Power Electronics, Drives and Energy Systems}, notes={Dec. 2006}, year={2006}, pages={1 - 4 }, abstract={The principles of a new technique using particle swarm algorithms for condition monitoring of the stator and rotor circuits of an induction machine is described in this paper. Using terminal voltage and current data, the stochastic optimization techn..... } } @inproceedings{ieeebib608, title={ The Modified Particle Swarm Optimization for Phase Balancing}, author = {Yutthapong Tuppadung and Werasak Kurutach}, booktitle={TENCON 2006. 2006 IEEE Region 10 Conference}, notes={Nov. 2006}, year={2006}, pages={1 - 4 }, abstract={This paper presents a new application of Particle Swarm Optimization (PSO) to an optimal phase arrangement in a radial distribution system. Most conventional methods that have been used to solve this kind of problem are based on trials and errors. In..... } } @inproceedings{ieeebib609, title={ Searching for Costas Arrays Using General Particle Swarm Optimization}, author = {Yin Xinchun and Liu Tao}, booktitle={TENCON 2006. 2006 IEEE Region 10 Conference}, notes={Nov. 2006}, year={2006}, pages={1 - 3 }, abstract={Costas arrays special permutation matrices have widespread applications in many fields such as signal processing and cryptography. However, so far the basic problem-the existence problem remains unsolved. To check the existence of costas arrays for a..... } } @inproceedings{ieeebib61, title={ Particle swarm optimizers for Pareto optimization with enhanced archiving techniques}, author = {T. Bartz-Beielstein and P. Limbourg and J. Mehnen and K. Schmitt and K.E. Parsopoulos and M.N. Vrahatis}, booktitle={The 2003 Congress on Evolutionary Computation, 2003. CEC '03}, notes={Volume 3, 8-12 Dec. 2003}, year={2003}, pages={1780 - 1787 Vol.3 }, abstract={During the last decade, numerous heuristic search methods for solving multi-objective optimization problems have been developed. Population oriented approaches such as evolutionary algorithms and particle swarm optimization can be distinguished into ..... } } @inproceedings{ieeebib610, title={ Maximum Likelihood DOA Estimation Using Particle Swarm Optimization Algorithm}, author = {Zeng jiankui and He zishu and Liu benyong}, booktitle={International Conference on Radar, 2006. CIE '06}, notes={Oct. 2006}, year={2006}, pages={1 - 4 }, abstract={Direction-of-arrival (DOA) estimation is an important problem. Many algorithms have been proposed. The Maximum Likelihood. (ML) is one of the good solutions. This paper presents an application of particle swarm optimization (PSO) developed for obtain..... } } @inproceedings{ieeebib611, title={ Adaptive Bandwidth Allocation Based on Particle Swarm Optimization for Multimedia LEO Satellite Systems}, author = {Dong Yan and Zhou Chi and Suo Siliang and Huang Zailu}, booktitle={First International Conference on Communications and Networking in China, 2006. ChinaCom '06}, notes={Oct. 2006}, year={2006}, pages={1 - 6 }, abstract={Bandwidth allocation becomes more crucial for efficient utilization of wireless resources to support multiple services in multimedia LEO communication networks and QoS diversities of services raise new challenges. This paper proposes an adaptive band..... } } @inproceedings{ieeebib612, title={ Stiffness Optimization of a 3-DOF Parallel Kinematic Machine Using Particle Swarm Optimization}, author = {Qingsong Xu and Yangmin Li}, booktitle={2006. ROBIO '06. IEEE International Conference on Robotics and Biomimetics}, notes={Dec. 2006}, year={2006}, pages={1169 - 1174}, abstract={In this paper, the architectural parameters optimization of a three-prismatic-universal-universal (3-PUU) parallel kinematic machine (PKM) with three translational degree-of-freedom (DOF) is performed using the efficient particle swarm optimization..... } } @inproceedings{ieeebib613, title={ A Particle Swarm Optimization Solution to NO2 and SO2 Emissions for Environmentally Constrained Economic Dispatch Problem}, author = {T. Thakur and Kanik Sem and Sumedha Saini and Sudhanshu Sharma}, booktitle={Transmission \& Distribution Conference and Exposition: Latin America, 2006. TDC '06. IEEE/PES}, notes={Aug. 2006}, year={2006}, pages={1 - 5 }, abstract={The environmentally constrained economic dispatch problem is a multi-objective nonlinear optimization problem with constraints. Until recently, this problem has been addressed by considering economic and emission objectives separately or as a weighte..... } } @inproceedings{ieeebib614, title={ Dynamic Null Steering in Linear Antenna Arrays Using Adaptive Particle Swarm Optimization Algorithm}, author = {Hassan M. Elkamchouchi and May Mansour Wagih}, booktitle={Third International Conference on Wireless and Mobile Communications, 2007. ICWMC '07}, notes={March 2007}, year={2007}, pages={24 - 24 }, abstract={In wireless applications the antenna pattern can be shaped in such way that it cancels interfering signals and produces a strong beam towards the wanted signal according to signal direction of arrival (DOA) by placing nulls in the direction of the in..... } } @inproceedings{ieeebib615, title={ Particle Swarm Optimization for Reconfigurable Sensor Electronics - Case Study: 3 Bit Flash ADC}, author = {Peter Tawdross and Andreas Konig}, booktitle={2006 International Workshop on Intelligent Solutions in Embedded Systems}, notes={June 2006}, year={2006}, pages={1 - 10 }, abstract={Sensor electronics is ubiquitous in embedded systems, yet its performance is susceptible to static and dynamic deviations. Even costly and time consuming laser trimming still canýýt deal with all the occurring deviations. Recently, analog reconfigura..... } } @inproceedings{ieeebib616, title={ Tradeoff Between Risk and Cost in Economic Dispatch Including Wind Power Penetration Using Particle Swarm Optimization}, author = {Lingfeng Wang and Chanan Singh}, booktitle={International Conference on Power System Technology, 2006. PowerCon 2006}, notes={Oct. 2006}, year={2006}, pages={1 - 7 }, abstract={A significant amount of attention has been paid to the renewable energy resources such as wind power in recent years. It has potential benefits in curbing emissions and reducing the consumption of irreplaceable fuel reserves. However, the penetration..... } } @inproceedings{ieeebib617, title={ Application of a Microhabitat Particle Swarm Algorithm in Transformer Substation Optimization}, author = {Fangjie Wu and Chengxue Zhang and JingChao Zhang and Zhiyuan Duan}, booktitle={International Conference on Power System Technology, 2006. PowerCon 2006}, notes={Oct. 2006}, year={2006}, pages={1 - 5 }, abstract={This paper provides a algorithm based on the microhabitat theory and particle swarm for the problem of Transformer Substation Optimiziation. This method can locate the substation according to muti-objects model of the problem, give the best scheme in..... } } @inproceedings{ieeebib618, title={ Parameter Identification for Position-based Robot Hand Tracking}, author = {Jong Kwang Lee and Hyo Jik Lee and Byung Suk Park and Ji Sup Yoon}, booktitle={SICE-ICASE, 2006. International Joint Conference}, notes={Oct. 2006}, year={2006}, pages={3063 - 3067 }, abstract={In this paper, we present a position-based robot hand tracking scheme where a pan-tilt camera is controlled such that a robot hand is always shown in the center of an image frame. We calculate the rotation angles of a pan-tilt camera by transforming ..... } } @inproceedings{ieeebib619, title={ Human Clustering for A Partner Robot Based on Particle Swarm Optimization}, author = {I.A. Sulistijono and N. Kubota}, booktitle={The 15th IEEE International Symposium on Robot and Human Interactive Communication, 2006. ROMAN 2006}, notes={Sept. 2006}, year={2006}, pages={686 - 691 }, abstract={This paper proposes swarm intelligence for a perceptual system of a partner robot. The robot requires the capability of visual perception to interact with a human. Basically, a robot should perform moving object extraction and clustering for visual p..... } } @inproceedings{ieeebib62, title={ AGC tuning of interconnected reheat thermal systems with particle swarm optimization}, author = {Y.L. Abdel-Magid and M.A. Abido}, booktitle={2003. ICECS 2003. Proceedings of the 2003 10th IEEE International Conference on Electronics, Circuits and Systems}, notes={Volume 1, 14-17 Dec. 2003}, year={2003}, pages={376 - 379 Vol.1}, abstract={This paper demonstrates the use of particle swarm optimization for optimizing the parameters of automatic generation control systems (AGC). An integral controller and a proportional-plus-integral controller are considered. A two-area reheat thermal s..... } } @inproceedings{ieeebib620, title={ Identification of Transcription Factor Binding Sites Using GA and PSO}, author = {Xiao-Yu Chang and Chun-Guang Zhou and Yan-Wen Li and Ping Hu}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 1, Oct. 2006}, year={2006}, pages={473 - 480 }, abstract={Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve this challenging issue. Under th..... } } @inproceedings{ieeebib621, title={ Urban Traffic Flow Forecasting Model of Double RBF Neural Network Based on PSO}, author = {Jianyu Zhao and Lei Jia and Yuehui Chen and Xudong Wang}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 1, Oct. 2006}, year={2006}, pages={892 - 896 }, abstract={The real time adaptive control of urban traffic, as a complex large system, usually needs to know the traffic of every intersection in advance. So traffic flow forecasting is a key problem in the real time adaptive control of urban traffic. This pape..... } } @inproceedings{ieeebib622, title={ Nonlinear System Identification of Hammerstien and Wiener Model Using Swarm Intelligence}, author = {J. Liu and Wenbo Xu and J. Sun}, booktitle={2006 IEEE International Conference on Information Acquisition}, notes={Aug. 2006}, year={2006}, pages={1219 - 1223}, abstract={In this paper a novel approach for nonlinear system identification is proposed using Particle Swarm Optimization (PSO) and Quantum-behaved Particle Swarm Optimization (QPSO). PSO and QPSO algorithm, the most successful and representative swarm intell..... } } @inproceedings{ieeebib623, title={ Particle Swarm Optimization for Route Planning of Unmanned Aerial Vehicles}, author = {Shibo Li and Xiuxia Sun and Yuejian Xu}, booktitle={2006 IEEE International Conference on Information Acquisition}, notes={Aug. 2006}, year={2006}, pages={1213 - 1218}, abstract={Route planning for unmanned aerial vehicle (UAV) is an extremely complex problem. Different means of optimization have been investigated for unmanned vehicles with various algorithms like genetic algorithms, evolution computations, neutral networks e..... } } @inproceedings{ieeebib624, title={ A Note on Particle Swarm Optimization: An integrated and theoretical approach}, author = {Chao-Wei Chou and Hsin-Hui Lin and Jiann-Horng Lin}, booktitle={2006 IEEE International Conference on Computational Cybernetics}, notes={Aug. 2006}, year={2006}, pages={1 - 6}, abstract={In this paper, a general and integrated form is proposed for the different kinds of particle swarm optimization. Also, some related theoretical results are given, including a convergence theorem for the random selection case and a lemma on probabilit..... } } @inproceedings{ieeebib625, title={ Circuit Synthesis Using Particle Swarm Optimization}, author = {C. Reis and J.A. Tenreiro Machado and A.M.S.F. Galhano and J. Boaventura Cunha}, booktitle={2006 IEEE International Conference on Computational Cybernetics}, notes={Aug. 2006}, year={2006}, pages={1 - 6}, abstract={Particle Swarm Optimization (PSO) is a population-based search algorithm that is initialized with a population of random solutions, called particles. In a PSO scheme each particle flies through the search space with a velocity that is adjusted dynami.....} } @inproceedings{ieeebib626, title={ Inferring Network Interactions using Recurrent Neural Networks and Swarm Intelligence}, author = {H.W. Ressom and Yuji Zhang and Jianhua Xuan and Yue Wang and R. Clarke}, booktitle={Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE}, notes={Aug. 2006}, year=2006, pages={4241 - 4244 }, abstract={We present a novel algorithm combining artificial neural networks and swarm intelligence (SI) methods to infer network interactions. The algorithm uses ant colony optimization (ACO) to identify the optimal architecture of a recurrent neural network .....} } @inproceedings{ieeebib627, title={ Programming Hierarchical TS Fuzzy Systems}, author = {Yuehui Chen and Lizhi Peng and A. Abraham}, booktitle={2006 International Symposium on Evolving Fuzzy Systems}, notes={Sept. 2006}, year={2006}, pages={157 - 162 }, abstract={In this paper, we focus on an evolutionary algorithm to design hierarchical or multilevel fuzzy system (architecture and parameters) automatically. This research work presents an automatic way of evolving hierarchical Takagi-Sugeno fuzzy systems TS-.....} } @inproceedings{ieeebib628, title={ An Improved Gaussian Dynamic Particle Swarm Optimization Algorithm}, author = {Qingjian Ni and Hancheng Xing}, booktitle={2006 International Conference on Computational Intelligence and Security}, notes={Volume 1, Nov. 2006}, year={2006}, pages={316 - 319 }, abstract={An improved Gaussian dynamic particle swarm optimization (PSO) algorithm is proposed in this paper. In the proposed version of PSO, the original swarm of particles is initialized by canonical PSO. The time varying linear inertial weight is reintroduc.....} } @inproceedings{ieeebib629, title={ A Particle Swarm Based Network Hosts Clustering Algorithm for Peer-to-Peer Networks}, author = {Yi Jiang and Jinyuan You and Xiaojian He}, booktitle={2006 International Conference on Computational Intelligence and Security}, notes={Volume 2, Nov. 2006}, year={2006}, pages={1176 - 1179 }, abstract={In this paper, we propose a particle swarm based algorithm to cluster peer-to-peer network hosts. Previously, the clustering of network hosts are mainly according to their connectivity [?], according to the RTTs between the hosts by probing each othe.....} } @inproceedings{ieeebib63, title={ DEPSO: hybrid particle swarm with differential evolution operator}, author = {Wen-Jun Zhang and Xiao-Feng Xie}, booktitle={2003. IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 4, 5-8 Oct. 2003}, year={2003}, pages={3816 - 3821 vol.4}, abstract={A hybrid particle swarm with differential evolution operator, termed DEPSO, which provide the bell-shaped mutations with consensus on the population diversity along with the evolution, while keeping the self-organized particle swarm dynamics, is prop..... } } @inproceedings{ieeebib630, title={ A Dynamical Particle Swarm Algorithm with Dimension Mutation}, author = {Jingxuan Wei and Yuping Wang}, booktitle={2006 International Conference on Computational Intelligence and Security}, notes={Volume 1, Nov. 2006}, year={2006}, pages={254 - 257 }, abstract={In this paper, a dynamical particle swarm algorithm with dimension mutation is proposed. First, we design a dynamically changing inertia weight based on the degree of both the particle diversity and the improvement of the best solutions in the succes.....} } @inproceedings{ieeebib631, title={ Social Decision Making with Multi-Relational Networks and Grammar-Based Particle Swarms}, author = {M.A. Rodriguez}, booktitle={40th Annual Hawaii International Conference on System Sciences, 2007. HICSS 2007}, notes={Jan. 2007}, year={2007}, pages={39 - 39 }, abstract={Social decision support systems are able to aggregate the local perspectives of a diverse group of individuals into a global social decision. This paper presents a multirelational network ontology and grammar-based particle swarm algorithm capable of.....} } @inproceedings{ieeebib632, title={ An Unsupervised Particle Swarm Optimization Classifier for SAR Image}, author = {Xiaohui Xu and An Zhang}, booktitle={2006 International Conference on Computational Intelligence and Security}, notes={Volume 2, Nov. 2006}, year={2006}, pages={1630 - 1634 }, abstract={Synthetic Aperture Radar (SAR) image classification is becoming increasingly important in military or scientific research. SAR image classification based on unsupervised learning usually requires optimization of some metrics. Local optimization techn.....} } @inproceedings{ieeebib633, title={ Thermal Process System Identification Using Particle Swarm Optimization}, author = {Ze Dong and Pu Han and Dongfeng Wang and Songming Jiao}, booktitle={2006 IEEE International Symposium on Industrial Electronics}, notes={Volume 1, July 2006}, year={2006}, pages={194 - 198 }, abstract={System identification adopting an open loop step response curve is a feasible way to obtain the mathematic model of the control object. Due to the satisfying performance in global optimization, evolution computing (EC) methods such as genetic algorit.....} } @inproceedings{ieeebib634, title={ Simple Rate Control Algorithm in TCP Network Using PSO}, author = {Tang Meiqin and Wang Haiqiang and Long Chengnian and Guan Xinping}, booktitle={Chinese Control Conference, 2006}, year={2006}, notes={Aug. 2006}, pages={1811 - 1814 }, abstract={This paper considers the rate control problem with the objective of maximizing the total user utility. It focuses on the inelastic traffic and removes restrictive assumptions on utility function. We propose a simple distributed algorithm using PSO (p.....)} } @inproceedings{ieeebib635, title={ Protective Relay Coordination for Micro-grid Operation Using Particle Swarm Optimization}, author = {H.H. Zeineldin and E.F. El-Saadany and M.M.A. Salama}, booktitle={2006 Large Engineering Systems Conference on Power Engineering}, notes={July 2006}, year={2006}, pages={152 - 157 }, abstract={With the increasing penetration of Distribution Generation (DG), micro-grid operation becomes an attractive and valuable option. In order for micro-grids to become a viable option, issues such as micro-grid control and protection must be addressed an.....} } @inproceedings{ieeebib636, title={ Feature-Level Fusion by Multi-Objective Binary Particle Swarm Based Unbiased Feature Selection for Optimized Sensor System Design}, author = {K. Iswandy and A. Koenig}, booktitle={2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems}, notes={Sept. 2006}, year={2006}, pages={365 - 370}, abstract={The performance of recognition systems in intelligent sensor technology can often be improved by using the combined information of several different measurement results, i.e., signal processing and feature computation, of singlesensr and/or multi-sen.....} } @inproceedings{ieeebib637, title={ Using an Improved Particle Swarm Optimization for Back Analysis of Geotechnical Parameters of Concrete Face Rock-fill Dams}, author = {Hao Du and ShiChun Chi and Feng Wang}, booktitle={Sixth International Conference on Hybrid Intelligent Systems, 2006. HIS '06}, notes={Dec. 2006}, year={2006}, pages={66 - 66 }, abstract={In this paper, an improved particle swarm optimizer (PSO) is applied to back analysis of geotechnical parameters of concrete face rock-fill dams (CFRD). This method uses the diverse coefficients in the different evolutionary strategies to prevent pre.....} } @inproceedings{ieeebib638, title={ Multiclass SVM Model Selection Using Particle Swarm Optimization}, author = {B.F. de Souza and A.C.P.L.F. de Carvalho and R. Calvo and R.P. Ishii}, booktitle={Sixth International Conference on Hybrid Intelligent Systems, 2006. HIS '06}, notes={Dec. 2006}, year={2006}, pages={31 - 31 }, abstract={Tuning SVM hyperparameters is an important step for achieving good classification performance. In the binary case, the model selection issue is well studied. For multiclass problems, it is harder to choose appropriate values for the base binary model.....} } @inproceedings{ieeebib639, title={ A Hybrid Rough Set--Particle Swarm Algorithm for Image Pixel Classification}, author = {S. Das and A. Abraham and S.K. Sarkar}, booktitle={Sixth International Conference on Hybrid Intelligent Systems, 2006. HIS '06}, notes={Dec. 2006}, year={2006}, pages={26 - 26 }, abstract={This article presents a framework to hybridize the rough set theory with a famous swarm intelligence algorithm known as Particle Swarm Optimization (PSO). The hybrid rough-PSO technique has been used for grouping the pixels of an image in its intensi.....} } @inproceedings{ieeebib64, title={ Bare bones particle swarms}, author = {J. Kennedy}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={80 - 87}, abstract={The particle swarm algorithm has just enough moving parts to make it hard to understand. The formula is very simple, it is even easy to describe the working of the algorithm verbally, yet it is very difficult to grasp in one's mind how the particles ..... } } @inproceedings{ieeebib640, title={ Particle Swarm Optimization of Feed-Forward Neural Networks with Weight Decay}, author = {M. Carvalho and T.B. Ludermir}, booktitle={Sixth International Conference on Hybrid Intelligent Systems, 2006. HIS '06}, notes={Dec. 2006}, year={2006}, pages={5 - 5 }, abstract={Training neural networks is a complex task of great importance in problems of supervised learning. In this work we analyze the use of the Particle Swarm Optimization algorithm and the cooperative variant with the weight decay mechanism for neural net.....} } @inproceedings{ieeebib641, title={ A Particle Swarm Algorithm for Multiobjective Design Optimization}, author = {E. Ochlak and B. Forouraghi}, booktitle={18th IEEE International Conference on Tools with Artificial Intelligence}, notes={Nov. 2006}, year={2006}, pages={765 - 772}, abstract={Many engineering design problems are characterized by presence of several conflicting objectives. This requires efficient search of the feasible design region for optimal solutions which simultaneously satisfy multiple design objectives. The search i.....} } @inproceedings{ieeebib642, title={ Hybrid Particle Guide Selection Methods in Multi-Objective Particle Swarm Optimization}, author = {D. Ireland and A. Lewis and S. Mostaghim and Jun Wei Lu}, booktitle={2006. e-Science '06. Second IEEE International Conference on e-Science and Grid Computing}, notes={Dec. 2006}, year={2006}, pages={116 - 116}, abstract={This paper presents quantitative comparison of the performance of different methods for selecting the guide particle for multi-objective particle swarm optimization (MOPSO). Two principal methods are compared: the recently described Sigma method, and.....} } @inproceedings{ieeebib643, title={ A Modified Particle Swarm Optimization for Solving Global Optimization Problems}, author = {Yi-Chao He and Kun-Qi Liu}, booktitle={2006 International Conference on Machine Learning and Cybernetics}, notes={Aug. 2006}, year={2006}, pages={2173 - 2177 }, abstract={This paper proposes a Modified Particle Swarm Optimization based on the combining Attractive and Repulsive operator with Function Stretching technique (for short MPSOwARS). This new algorithm utilizes adequately the characters that the Attractive and.....} } @inproceedings{ieeebib644, title={ Hybrid Quantum Evolutionary Algorithms Based on Particle Swarm Theory}, author = {Yang Yu and Yafei Tian and Zhifeng Yin}, booktitle={2006 1ST IEEE Conference on Industrial Electronics and Applications}, note={May 2006}, year={2006}, pages={1 - 7 }, abstract={Inspired by the idea of hybrid optimization algorithms, this paper proposes two hybrid quantum evolutionary algorithms (QEA) based on combining QEA with particle swarm optimization (PSO) to improve the performance of QEA. The main idea of the first m.....} } @inproceedings{ieeebib645, title={ Smooth Path Planning of a Mobile Robot Using Stochastic Particle Swarm Optimization}, author = {Xin Chen and Yangmin Li}, booktitle={Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation}, notes={June 2006}, year={2006}, pages={1722 - 1727}, abstract={This paper proposes a new approach using improved particle swarm optimization (PSO) to optimize the path of a mobile robot through an environment containing static obstacles. Relative to many optimization methods that produce nonsmooth paths, the PSO.....} } @inproceedings{ieeebib646, title={ Design of Fractional Order Controllers Based on Particle Swarm Optimization}, author = {Jun-yi Cao and Bing-gang Cao}, booktitle={2006 1ST IEEE Conference on Industrial Electronics and Applications}, note={May 2006}, year={2006}, pages={1 - 6 }, abstract={An intelligent optimization method for designing Fractional Order PID (FOPID) controllers based on Particle Swarm Optimization (PSO) is presented in this paper. Fractional calculus can provide novel and higher performance extension for FOPID controll.....} } @inproceedings{ieeebib647, title={ Spatial Information Based Image Segmentation Using a Modified Particle Swarm Optimization Algorithm}, author = {S. Das and A. Abraham and A. Konar}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={438 - 444 }, abstract={This article proposes a particle swarm based segmentation algorithm for automatically grouping the pixels of an image into different homogeneous regions. In contrast to most of the existing evolutionary image segmentation techniques, we have incorpor.....} } @inproceedings{ieeebib648, title={ The Particle Swarm: Individual and Collective Intelligence}, author = {J. Kennedy}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 1, Oct. 2006}, year={2006}, pages={xxxv - xxxv }, abstract={Western psychology has traditionally focused on processes considered to be internal or private to the individual, with the social world generally regarded as an aspect of "the environment." Recent cross-cultural psychological research reveals fundame.....} } @inproceedings{ieeebib649, title={ Particle Swarm Optimization-Based SVM Application: Power Transformers Incipient Fault Syndrome Diagnosis}, author = {Tsair-Fwu Lee and Ming-Yuan Cho and Chin-Shiuh Shieh and Fu-Min Fang}, booktitle={International Conference on Hybrid Information Technology, 2006. ICHIT '06. Vol1}, notes={Volume 1, Nov. 2006}, year={2006}, pages={468 - 472 }, abstract={Based on statistical learning theory, Support Vector Machine (SVM) has been well recognized as a powerful computational tool for problems with nonlinearity had high dimensionalities. In this paper, we present a successful adoption of the particle swa.....} } @inproceedings{ieeebib65, title={ Visualizing particle swarm optimization - Gaussian particle swarm optimization}, author = {B.R. Secrest and G.B. Lamont}, booktitle={the 2003 IEEE Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of}, notes={24-26 April 2003}, year={2003}, pages={198 - 204}, abstract={Particle swarm optimization (PSO) conjures an image of particles searching for the optima the way bees buzz around flowers. One approach at visualizing the swarm graphs where all the particles are each generation, thus demonstrating the random nature..... } } @inproceedings{ieeebib650, title={ Task Scheduling Based on PSO Algorithm in Computational Grid}, author = {Lei Zhang and Yuehui Chen and Bo Yang}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={696 - 704 }, abstract={Task scheduling is a key problem concerned in computational grid. In this paper, a heuristic approach based on particle swarm optimization is adopted to solving scheduling problem in grid environment. Each particle is represented a possible solution,.....} } @inproceedings{ieeebib651, title={ A Particle Swarm and Chaos Combination Approach for Vehicle Simulator Optimization}, author = {Qiang Zhao and Fang Gao}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={986 - 994 }, abstract={Mechanism design is one crucial step in vehicle simulator developing. A combined approach of particle swarm optimization (PSO) algorithm and mutative scale chaos search algorithm is proposed for the parameters optimization of motion mechanism of vehi.....} } @inproceedings{ieeebib652, title={ An Enhanced Hybrid Quadratic Particle Swarm Optimization}, author = {Tan Ying and Ya-ping Yang and Jian-chao Zeng}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={980 - 985 }, abstract={Particle swarm optimization (PSO) is swarm-based stochastic optimization originating from artificial life and evolutionary computation. The algorithm completes the optimization through following the personal best solution of each particle and the glo.....} } @inproceedings{ieeebib653, title={ Task Scheduling in Grid Based on Particle Swarm Optimization}, author = {Tingwei Chen and Bin Zhang and Xianwen Hao and Yu Dai}, booktitle={The Fifth International Symposium on Parallel and Distributed Computing, 2006. ISPDC '06}, notes={July 2006}, year={2006}, pages={238 - 245 }, abstract={Task scheduling is one of the core steps to effectively exploit the capabilities of resources in the Grid. The task scheduling problem is an NP-complete problem. This paper studied on the task scheduling problem in grid environment and proposed a tas.....} } @inproceedings{ieeebib654, title={ Particle Swarm Algorithm for Tasks Scheduling in Distributed Heterogeneous System}, author = {Xiaohong Kong and Jun Sun and Wenbo Xu}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={690 - 695 }, abstract={A distributed heterogeneous system consists of a suite of processors or machines with different processing capacities. It can be performance-to-cost efficient to meet the diverse computation requirements if properly deployed. Task scheduling is a cru.....} } @inproceedings{ieeebib655, title={ A New Particle Swarm Optimization Algorithm for Short-Term Scheduling of Single-Stage Batch Plants with Parallel Lines}, author = {Jin Zhu and Xingsheng Gu}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={673 - 678 }, abstract={This paper proposes a new particle swarm optimization (NPSO) algorithm to short-term scheduling of single-stage batch plants with parallel units using the continuous-time domain representation. The model is formulated as a mixed-integer linear progra.....} } @inproceedings{ieeebib656, title={ Particle Swarm Approach to Scheduling Work-Flow Applications in Distributed Data-Intensive Computing Environments}, author = {Hongbo Liu and Shichang Sun and A. Abraham}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={661 - 666 }, abstract={The scheduling problem in distributed data-intensive computing environments has been an active research topic due to immense practical applications. In this paper, we model the scheduling problem for work-Flow applications in distributed Data-intensi.....} } @inproceedings{ieeebib657, title={ Particle Swarm Extension to LOLIMOT}, author = {R. Mehran and A. Fatehi and C. Lucas and B.N. Araabi}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={969 - 974 }, abstract={In this paper, we will present population based method for placement of center of radial basis function of a locally linear neuro-fuzzy (LLNF) network, which is trained by LOLIMOT algorithm. Originally, LOLIMOT algorithm incrementally divides the hyp.....} } @inproceedings{ieeebib658, title={ Particle Swarm Algorithm for Classification Rules Generation}, author = {Xianzhang Zhao and Junfang Zeng and Yibo Gao and Yiping Yang}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={957 - 962 }, abstract={It is the core problem in building a fuzzy classification system to extract an optimal group of fuzzy classification rules from fuzzy data set. A new kind of algorithm is proposed for fuzzy rules' generating in this work. The idea behind the algorith.....} } @inproceedings{ieeebib659, title={ Particle Swarm Optimization Based Algorithm for Bilevel Programming Problems}, author = {Zhigang Zhao and Xinyi Gu}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={951 - 956 }, abstract={A bilevel programming (BLP) problem is a NP hard problem that is very hard to be solved. The existing solution algorithms or methods designed to solve the particular BLP problems are inefficient and lack of universality. In this paper, a modified par.....} } @inproceedings{ieeebib66, title={ Tracking and optimizing dynamic systems with particle swarms}, author = {R.C. Eberhart and Yuhui Shi}, booktitle={Proceedings of the 2001 Congress on Evolutionary Computation, 2001}, notes={Volume 1, 27-30 May 2001}, year={2001}, pages={94 - 100 vol. 1 }, abstract={Using particle swarms to track and optimize dynamic systems is described. Issues related to tracking and optimizing dynamic systems are briefly reviewed. Three kinds of dynamic systems are defined for the purposes of this paper. One of them is chosen..... } } @inproceedings{ieeebib660, title={ Combination Artificial Ant Clustering and K-PSO Clustering Approach to Network Security Model}, author = {S. Srinoy and W. Kurutach}, booktitle={International Conference on Hybrid Information Technology, 2006. ICHIT'06. Vol 2}, notes={Volume 2, Nov. 2006}, year={2006}, pages={128 - 134 }, abstract={A Computer system now operate in an environment of near ubiquitous connectivity, whether tethered to an Ethernet cable or connected via wireless technology. While the availability of always on communication has created countless new opportunities for.....} } @inproceedings{ieeebib661, title={ Loss Power Minimization Using Particle Swarm Optimization}, author = {A.A.A. Esmin and G. Lambert-Torres}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={1988 - 1992 }, abstract={This paper presents a particle swarm optimization (PSO) as an efficient approach for loss reduction study. This issue can be formulated as a nonlinear optimization problem. The proposed approach employs the PSO algorithm for optimal setting of Optima.....} } @inproceedings{ieeebib662, title={ Design of Optimal PI Controllers for Doubly Fed Induction Generators Driven by Wind Turbines Using Particle Swarm Optimization}, author = {Wei Qiao and G.K. Venayagamoorthy and R.G. Harley}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={1982 - 1987 }, abstract={When subjected to transient disturbances in the power grid, the variable frequency converter (VFC) is the most sensitive part in the variable-speed wind turbine generator system (WTGS) equipped with a doubly fed induction generator (DFIG). The VFC is.....} } @inproceedings{ieeebib663, title={ Application of Particle Swarm Optimization to PMSM Stator Fault Diagnosis}, author = {Li Liu and D.A. Cartes and Wenxin Liu}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={1969 - 1974 }, abstract={Permanent Magnet Synchronous Motors (PMSM) are frequently used to high performance applications. Accurate diagnosis of incipient faults can significantly improve system availability and reliability. This paper proposes a new scheme for the automatic .....} } @inproceedings{ieeebib664, title={ Comparison of different hybridization strategies in evolutionary optimization for EM}, author = {F. Grimaccia and M. Mussetta and R.E. Zich}, booktitle={Antennas and Propagation Society International Symposium 2006, IEEE}, notes={9-14 July 2006}, year={2006}, pages={585 - 588 }, abstract={The genetical swarm optimization (GSO) is the integration of the genetic algorithm (GA) and particle swarm optimization (PSO). The key feature of this algorithm is that it maintains the integration of GA and PSO for the entire run. In this paper the .....} } @inproceedings{ieeebib665, title={ Particle Swarm Optimization of Fuzzy ARTMAP Parameters}, author = {E. Granger and P. Henniges and L.S. Oliveira and R. Sabourin}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={2060 - 2067 }, abstract={In this paper a Particle Swarm Optimization (PSO)-based training strategy is introduced for fuzzy ARTMAP that minimizes generalization error while optimizing parameter values. Through a comprehensive set simulations, it has been shown that this train.....} } @inproceedings{ieeebib666, title={ Design of Multi-Band Transmission Line Transformer using Particle Swarm Optimization}, author = {M. Khodier and N. Dib}, booktitle={Antennas and Propagation Society International Symposium 2006, IEEE}, notes={9-14 July 2006}, year={2006}, pages={3305 - 3308 }, abstract={The design of N-section matching transformer operating at N arbitrary frequencies using the particle swarm optimization (PSO) method is demonstrated. Although analytical methods based on standard transmission line theory can be used in such designs, .....} } @inproceedings{ieeebib667, title={ A two-step strategy for a multi-scaling inversion of phaseless measurements of the total field}, author = {R. Azaro and D. Franceschini and G. Franceschini and L. Manica and A. Massa}, booktitle={Antennas and Propagation Society International Symposium 2006, IEEE}, notes={9-14 July 2006}, year={2006}, pages={1073 - 1076 }, abstract={This work presents an innovative two-step methodology for the electromagnetic imaging from amplitude-only measurements of the total field. At the first stage, an inverse source algorithm is used to estimate the distribution of the incident field insi.....} } @inproceedings{ieeebib668, title={ Online Training of a Generalized Neuron with Particle Swarm Optimization}, author = {R. Kiran and S.R. Jetti and G.K. Venayagamoorthy}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={5088 - 5095 }, abstract={Neural networks are used in a wide number of fields including signal and image processing, modeling and control and pattern recognition. Some of the most common type of neural networks is the multilayer perceptrons and the recurrent neural networks. .....} } @inproceedings{ieeebib669, title={ PSO-PID: a novel controller for AQM routers}, author = {Xiuli Wang and Yongji Wang and Hui Zhou and Xiaoyong Huai}, booktitle={2006 IFIP International Conference on Wireless and Optical Communications Networks}, notes={11-13 April 2006}, year={2006}, pages={5 pp. }, abstract={This paper presents an improved TCP/active queue management (AQM) model and a novel AQM control system, called particle swarm optimization (PSO) proportional-integral-differential (PID) controller, under large-delay network situations. First, we pres.....} } @article{ieeebibJ67, title={ A multiagent-based particle swarm optimization approach for optimal reactive power dispatch}, author={B. Zhao and C.X. Guo and Y.J. Cao}, journal={IEEE Transactions on Power Systems}, volume= 20, issue= 2, date={ May 2005}, pages={1070 - 1078 }, year={2005}, abstract={Reactive power dispatch in power systems is a complex combinatorial optimization problem involving nonlinear functions having multiple local minima and nonlinear and discontinuous constraints. In this paper, a solution to the reactive power dispatch ..... } } @inproceedings{ieeebib670, title={ Optimization of a reflectarray antenna via hybrid evolutionary algorithms}, author = {F. Grimaccia and M. Mussetta and P. Pirinoli and R.E. Zich}, booktitle={17th International Zurich Symposium on Electromagnetic Compatibility, 2006. EMC-Zurich 2006}, notes={27 Feb.-3 March 2006}, year={2006}, pages={254 - 257 }, abstract={In this paper a new effective optimization algorithm called genetical swarm optimization (GSO) will be presented. It has been developed in order to combine in the most effective way the properties of two of the most popular evolutionary optimization .....} } @inproceedings{ieeebib671, title={ Application of PSO technique for optimal location of FACTS devices considering system loadability and cost of installation}, author = {M. Saravanan and S.M.R. Slochanal and P. Venkatesh and P.S. Abraham}, booktitle={Power Engineering Conference, 2005. IPEC 2005. The 7th International}, notes={29 Nov.-2 Dec. 2005}, year={2005}, pages={716 - 721 Vol. 2 }, abstract={This paper presents the application of particle swarm optimization (PSO) technique to find optimal location of flexible AC transmission system (FACTS) devices to achieve maximum system loadability with minimum cost of installation of FACTS devices. W.....} } @inproceedings{ieeebib672, title={ K-means Algorithm Based on Particle Swarm Optimization Algorithm for Anomaly Intrusion Detection}, author = {Lizhong Xiao and Zhiqing Shao and Gang Liu}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={5854 - 5858 }, abstract={K-means as a clustering algorithm has been studied in intrusion detection. However, with the deficiency of global search ability it is not satisfactory. Particle swarm optimization (PSO) is one of the evolutionary computation techniques based on swar.....} } @inproceedings{ieeebib673, title={ A Scheduling Holon Model with Time Petri Net and Its Solution With A Novel PSO-GA Algorithm}, author = {Yunping Yao and Youtang Li and Fuqing Zhao and Yahong Yang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6616 - 6620 }, abstract={Holonic manufacturing is a highly distributed control paradigm based on a kind of autonomous and cooperative entity called "holon". It can both guarantee performance stability, predictability and global optimization of hierarchical control, and provi.....} } @inproceedings{ieeebib674, title={ PSO Based Surrogate Model Steady State Optimization with Its application}, author = {Xiugai Li and Dexian Huang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6578 - 6582 }, abstract={RBF neural network based surrogate model is constructed from process simulator and Particle Swarm Optimization (PSO) strategy is discussed to solve this nonlinear programming problem with some output variables are unmeasured. Performance of maximum y.....} } @inproceedings{ieeebib675, title={ Personalized On-line Service of Particle Swarm Optimization Cluster Analysis Algorithm}, author = {Jun Wang and Xiang Yang Li}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6073 - 6077 }, abstract={To provide accurate and personalized information service, a K-Median cluster analysis of parallel particle swarm optimization(PSO) and simulated annealing(SA) algorithm was proposed to cluster the information resource in the network. The algorithm in.....} } @inproceedings{ieeebib676, title={ Particle Swarm Optimization for Fuzzy c-Means Clustering}, author = {Li Wang and Yushu Liu and Xinxin Zhao and Yuanqing Xu}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6055 - 6058 }, abstract={A new Fuzzy c-Means Clustering Algorithm based on Particle Swarm Optimization (PSOFCM) is presented after analyzing the advantages and disadvantages of the classical fuzzy c-means clustering algorithm. It avoids the local optima, and also is robust t.....} } @inproceedings{ieeebib677, title={ Design A Novel Neural Network Clustering Algorithm Based on PSO and Application}, author = {Hongwen Yan and Rui Ma}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6015 - 6018 }, abstract={This paper presents a novel parallel neural network clustering approach based Particle Swarm Optimisation (PSO) for the large spatial database suitable in data mining. A large number of pieces of evidence are clustered into subsets, a nonlinear conne.....} } @inproceedings{ieeebib678, title={ Study of Strip Flatness and Gauge Complex Control Based on Improved PSO-RBF Neural Networks}, author = {Lin Xu and Xiaoke Fang and Qichao Fang and Jianhui Wang and Shusheng Gu}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={6397 - 6400 }, abstract={An improved particle swarm optimization (IPSO) is presented to solve the premature and low precision based on shrinking chaotic mutation with population's fitness, which is used to train the radius basis function (RBF) neural networks, and optimizati.....} } @inproceedings{ieeebib679, title={ Using Particle Swarm Optimization and Genetic Programming to Evolve Classification Rules}, author = {Liping Yan and Jianchao Zeng}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3415 - 3419 }, abstract={According to analyzing particle swarm optimization (PSO), the structure of Genetic Programming (GP) and classifier model, PSO algorithm and GP were made to combine to evolve classification rules. Rules were described as binary tree which non-leaf nod.....} } @article{ieeebibJ68, title={ Dynamic security border identification using enhanced particle swarm optimization}, author={I.N. Kassabalidis and M.A. El-Sharkawi and , R.J., II Marks and L.S. Moulin and A.P. Alves da Silva}, journal={IEEE Transactions on Power Systems}, volume= 17, issue= 3, date={ Aug. 2002}, pages={723 - 729 }, year={2002}, abstract={The ongoing deregulation of the energy market increases the need to operate modern power systems close to the security border. This requires enhanced methods for the vulnerability border tracking. The high-dimensional nature of power systems' operati..... } } @inproceedings{ieeebib680, title={ A Solution to Unit Commitment Problem by ACO and PSO Hybrid Algorithm}, author = {Gang Xiao and Shouzhi Li and Xuanhong Wang and Rui Xiao}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7475 - 7479 }, abstract={To solve the mixed-integer nonlinear programming problem of unit commitment in electric power system, the problem was separated into two subordinate optimization problems with integral and continuous variables first, then a new hybrid algorithm based.....} } @inproceedings{ieeebib681, title={ A New Combinatorial Meta-heuristic Algorithm for Stochastic Electric Power System Production Costing and Operations Planning}, author = {Baozheng Liu and Ping Ren and Liqun Gao and Nan Li}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7429 - 7433 }, abstract={This paper presents a new method----modified particle swarm optimization (PSO) for stochastic electric power system production costing and operations planning. In this method we formulate a stochastic in which unit availability and system load demand.....} } @inproceedings{ieeebib682, title={ Research and Simulation of Fuzzy Controller Design Based on Particle Swarm Optimization}, author = {Yufei Zhang and Z. Dang and Jie Wei}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3757 - 3761 }, abstract={When complexity of control object is increased, the design of fuzzy controller becomes difficult by experts experience. A new design method of fuzzy controller by Particle Swarm Optimization (PSO) is supposed, which can optimize rules and membership .....} } @inproceedings{ieeebib683, title={ A Novel Approach to Image Fusion Based on Multi-Objective Optimization}, author = {Yifeng Niu and Lincheng Shen}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={9911 - 9915 }, abstract={Most approaches to image fusion determine the building of image fusion model based on experience, and the parameter configuration of the fusion model is somewhat arbitrary. In this paper, a novel approach to image fusion based on multi-objective opti.....} } @inproceedings{ieeebib684, title={ Particle Swarm Optimization Combined with Chaotic and Gaussian Mutation}, author = {Dongli Jia and Lihong Li and Yongqiang Zhang and Xiangguo Chen}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3281 - 3285 }, abstract={Chaotic and Gaussian Mutation Particle Swarm Optimization (CGPSO) was proposed to solve the premature and low optimizing precision in standard PSO. In the earlier iterative phase, chaotic mutation was introduced to avoid optimization being trapped in.....} } @inproceedings{ieeebib685, title={ A Quadratic Particle Swarm Optimization and its Self-Adaptive Parameters}, author = {Yaping Yang and Ying Tan and Jianchao Zeng}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3265 - 3270 }, abstract={Particle Swarm Optimization(PSO) is a kind of random optimization algorithm based on the swarm intelligence. This paper presents a Quadratic PSO by improving the standard PSO's evolution equation on the foundation of analyzing standard PSO's model an.....} } @inproceedings{ieeebib686, title={ A Learning Algorithm of Artificial Neural Network Based on GA - PSO}, author = {Shiqiang Du and Wanshe Li and Kai Cao}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3633 - 3637 }, abstract={In order to get over the insufficiency of back-propagation (BP) algorithm, after analyses of genetic algorithm (GA) and particle swarm optimization (PSO), a GAPSO algorithm is proposed. In GAPSO, individuals in a new generation are crea.....} } @inproceedings{ieeebib687, title={ The Application of Magnet Optimization of Permanent Magnet Synchronous Motor by Modified PSO}, author = {Chen Dongyang and Sun Changzhi and An Yuejun}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={1879 - 1882 }, abstract={The permanent magnet motor price is mostly decided by permanent magnet usage. Particle swarm optimization (PSO) keeps fast convergence and improved accuracy after adding logistic mapping. The 3 phase permanent magnet synchronous motor is optimized by.....} } @inproceedings{ieeebib688, title={ Application of Neural Network Based on PSO Algorithm in Prediction Model for Dissolved Oxygen in Fishpond}, author = {Changhui Deng and XinJiang Wei and LianXi Guo}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={9401 - 9405 }, abstract={Based on the study of affected factors for Dissolved oxygen (DO) concentration in fishpond, a fuzzy neural network prediction model for DO in fishpond was proposed utilizing the nice approximation ability of fuzzy neural network to given nonlinear sy.....} } @inproceedings{ieeebib689, title={ Study on Power System Load Forecasting Based on MPSO Artificial Neural Networks}, author = {Wei Liu and KejunWang and Mo Tang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={2728 - 2732 }, abstract={As a representative method of swarm intelligence particle swarm optimization(PSO) is an algorithm for search the multidimensional complex space through cooperation and competition among the individuals in a population of particles. A novel modified p.....} } @article{ieeebibJ69, title={ A Cooperative approach to particle swarm optimization}, author={F. van den Bergh and A.P. Engelbrecht}, journal={IEEE Transactions on Evolutionary Computation}, volume= 8, issue= 3, date={ June 2004}, pages={225 - 239 }, year={2004}, abstract={The particle swarm optimizer (PSO) is a stochastic, population-based optimization technique that can be applied to a wide range of problems, including neural network training. This paper presents a variation on the traditional PSO algorithm, called t..... } } @inproceedings{ieeebib690, title={ Partially Random Learning Particle Swarm Optimization with Parameter Adaptation}, author = {Yuejian Xu and Xinmin Dong and Kaijun Liao}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3519 - 3523 }, abstract={A modified particle swarm optimization (PSO) with new parameter learning strategy is presented. During the running time, the inertial weight is adaptively adjusted by proportion coefficient. By introducing random learning strategy, the searching scop.....} } @inproceedings{ieeebib691, title={ A Survey on Application of Swarm Intelligence Computation to Electric Power System}, author = {Hua Bai and Bo Zhao}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7587 - 7591 }, abstract={Swarm intelligence computation is becoming an important topic in the field of artificial intelligence, and is successfully applied in a lot of fields, which is indicating fairly great potential for development. Recently, there are abundant reports on.....} } @inproceedings{ieeebib692, title={ Application of PSO-based ANN in Knowledge Acquisition for the Selection of Optimal Milling Parameters}, author = {Xiankun Lin and Aiping Li and Weimin Zhang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 2, 21-23 June 2006}, year={2006}, pages={7992 - 7996 }, abstract={In NC milling processes, optimal cutting parameters have a great influence on reducing the production cost and time and improving the product quality. In this paper, a particle swarm optimization (PSO) based artificial neural network (ANN) is propose.....} } @inproceedings{ieeebib693, title={ The Nonholonomic Motion Planning and Control of the Unicycle Mobile Robot}, author = {Jin Zhiyong and Zhang Qizhi}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3461 - 3465 }, abstract={The nonholonomic motion planning and control of a unicycle robot was studied and a new algorithm was proposed. The problem of optimal control in infinite dimension space was converted to the problem in finite dimension space by parameterizing the con.....} } @inproceedings{ieeebib694, title={ A two-order Particle Swarm Optimization Model and the Selection of its Parameters}, author = {Jianxiu Hu and Jianchao Zeng and Yaping Yang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3440 - 3445 }, abstract={Based on the analysis of theoretical model and evolutionary equations for the standard PSO, a new particle swarm optimization model, called the two-order PSO, was performed, which simulated more precisely the velocity change of particles than the sta.....} } @inproceedings{ieeebib695, title={ A Predictive Model of Sinter Chemical Composition and Its Application}, author = {Jiesheng Wang and Wei Wang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={4856 - 4860 }, abstract={It is necessary to predict sinter quality in order to realize optimization of technology parameters in sintering process. A predictive model is proposed by combining hybrid Takagi-Sugeno fuzzy model and particle swarm optimization algorithm to predic.....} } @inproceedings{ieeebib696, title={ The Meteorological Prediction Model Study of Neural Ensemble Based on PSO Algorithms}, author = {Jiansheng Wu and Lingzhi Wang and Baoxiang Zhu}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={51 - 55 }, abstract={This paper presents the evolving neural network architecture and beginning connection weights based on particle swarm optimization algorithms in order to produces the better network architecture and beginning connection weights, trains again the trad.....} } @inproceedings{ieeebib697, title={ The Kalman Particle Swarm Optimization Algorithm and Its Application in Soft-sensor of Acrylonitrile Yield}, author = {Guo Wei and Chen Guo-chu and Yu Jin-shou}, booktitle={International Conference on Neural Networks and Brain, 2005. ICNN\&B '05}, notes={Volume 1, 13-15 Oct. 2005}, year={2005}, pages={124 - 127 }, abstract={This paper proposes the Kalaman Particle Swarm Optimization Algorithm (KPSO), which combines the Kalman Filter and PSO. KPSO assumes that particle moves according to the Kalman Filer. The comparison of optimization performance between KPSO and PSO to.....} } @inproceedings{ieeebib698, title={ A Modified Particle Swarm Optimization Algorithm and its Application For Solving Traveling Salesman Problem}, author = {Cuiru Wang and Jiangwei Zhang and Jing Yang and Chaoju Hu and Jun Liu}, booktitle={International Conference on Neural Networks and Brain, 2005. ICNN\&B '05}, notes={Volume 2, 13-15 Oct. 2005}, year={2005}, pages={689 - 694 }, abstract={A modified particle swarm optimization (MPSO) algorithm was proposed. In the modified algorithm, the cooperative mechanism among individuals has been introduced, namely, particles not only adjust its own flying speed according to itself and the best .....} } @inproceedings{ieeebib699, title={ FIR Digital Filters Design Based on Quantum-behaved Particle Swarm Optimization}, author = {Wei Fang and Jun Sun and Wenbo Xu and Jing Liu}, booktitle={First International Conference on Innovative Computing, Information and Control, 2006. ICICIC '06}, notes={Volume 1, 30-01 Aug. 2006}, year={2006}, pages={615 - 619 }, abstract={FIR digital filters design involves multi-parameter optimization, on which the existing optimization algorithm doesnt work efficiently. This paper focuses on employing the proposed Quantum-behaved Particle Swarm Optimization (QPSO) to design FI.....} } @article{ieeebibJ7, title={ An approach to multimodal biomedical image registration utilizing particle swarm optimization}, author = {M.P. Wachowiak and R. Smolikova and Yufeng Zheng and J.M. Zurada and A.S. Elmaghraby}, journal={IEEE Transactions on Evolutionary Computation}, volume= 8, issue= 3, date={ June 2004}, pages={289 - 301 }, year={2004}, abstract={Biomedical image registration, or geometric alignment of two-dimensional and/or three-dimensional (3D) image data, is becoming increasingly important in diagnosis, treatment planning, functional studies, computer-guided therapies, and in biomedical r..... } } @inproceedings{ieeebib70, title={ Load-frequency control by hybrid evolutionary fuzzy PI controller}, author = {C.-F. Juang and C.-F. Lu}, booktitle={Generation, Transmission and Distribution, IEE Proceedings-}, notes={Volume 153, Issue 2, 16 March 2006}, year={2006}, pages={196 - 204 }, abstract={Power-system load-frequency control by fuzzy-PI (FPI) controller is proposed. During control, a fuzzy system is used to decide adaptively the proper proportional and integral gains of a PI controller according the area-control error and its change. T.....} } @inproceedings{ieeebib700, title={ Particle Swarm Optimization for Image Noise Cancellation}, author = {Yue-Cheng Chen and Hsin-Chih Wang and Te-Jen Su}, booktitle={First International Conference on Innovative Computing, Information and Control, 2006. ICICIC '06}, notes={Volume 1, 30-01 Aug. 2006}, year={2006}, pages={587 - 590 }, abstract={In this paper, a novel method for designing templates of cellular neural network to cancel the image noise is discussed. The discrete-time cellular neural network (DTCNN) combining with particle swarm optimization (PSO) is applied to image noise canc.....} } @inproceedings{ieeebib701, title={ PSO based single strategy risk programming problem for virtual enterprise}, author = {Min Huang and Xuejing Wu and Xingwei Wang and W.H.I.P.K.L. Yung}, booktitle={American Control Conference, 2006}, year={2006}, notes={14-16 June 2006}, pages={5 pp. }, abstract={Virtual enterprise will be the main organization mode for enterprises in information society of twenty-one century. Focus on the fuzzy characteristics and project organization mode of virtual enterprises, the risk programming methods for virtual ente.....} } @inproceedings{ieeebib702, title={ A novel training algorithm in ANFIS structure}, author = {M.A. Shoorehdeli and M. Teshnehlab and A.K. Sedigh}, booktitle={American Control Conference, 2006}, year={2006}, notes={14-16 June 2006}, pages={6 pp. }, abstract={This paper introduces a new hybrid approach for training the adaptive network based fuzzy inference system (ANFIS). The previous works emphasized on gradient base method or least square (LS) based method. In this study we apply one of the swarm intel.....} } @inproceedings{ieeebib703, title={ Multi-Objective Particle Swarm Optimization Algorithm Based on Enhanced µ -Dominance}, author = {Jiang Hao and Zheng Jin-hua and Chen liang-jun}, booktitle={2006 IEEE International Conference on Engineering of Intelligent Systems}, notes={22-23 April 2006}, year={2006}, pages={1 - 5}, abstract={In this paper, we describe a multi-objective particle swarm optimization algorithm (MOPSO) that incorporates the concept of the enhanced µ -dominance, we present this new concept to update the archive, the archiving technique can help us to main.....} } @inproceedings{ieeebib704, title={ Sensor Scheduling For Target Tracking Using Particle Swarm Optimization}, author = {S. Maheswararajah and S. Halgamuge}, booktitle={Vehicular Technology Conference, 2006. VTC 2006-Spring. IEEE 63rd}, notes={Volume 2, 2006}, year={2006}, pages={573 - 577 }, abstract={This paper presents a new solution to the problem of optimal sensor scheduling for tracking a target with several noisy sensor measurements. The state of the target is modeled as a linear Gaussian model and the measurements are assumed linearly relat.....} } @inproceedings{ieeebib705, title={ Reliability Growth Modeling for Software Fault Detection Using Particle Swarm Optimization}, author = {A. Sheta}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={3071 - 3078 }, abstract={Modeling the software testing process to obtain the predicted faults (failures) depends mainly on representing the relationship between execution time (or calendar time) and the failure count or accumulated faults. A number of unknown function parame.....} } @inproceedings{ieeebib706, title={ An Efficient Particle Swarm Optimization Approach Based on Cultural Algorithm Applied to Mechanical Design}, author = {L. dos Santos Coelho and V.C. Mariani}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1099 - 1104 }, abstract={Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the swarm intelligence theory, this paper dis.....} } @inproceedings{ieeebib707, title={ Constrained Single-Objective Optimization Using Particle Swarm Optimization}, author = {K. Zielinski and R. Laur}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={443 - 450 }, abstract={Particle Swarm Optimization (PSO) is an optimization method that is derived from the behavior of social groups like bird flocks or fish schools. In this work PSO is used for the optimization of the constrained test suite of the special session on con.....} } @inproceedings{ieeebib708, title={ In Search of the Essential Particle Swarm}, author = {J. Kennedy}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1694 - 1701 }, abstract={The particle swarm algorithm is broken down into its essential steps, and alternative interpretations of those steps are proposed. New versions that perform well on a suite of test functions are developed......} } @inproceedings{ieeebib709, title={ Diversity-based Information Exchange among Multiple Swarms in Particle Swarm Optimization}, author = {G.G. Yen and M. Daneshyari}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1686 - 1693 }, abstract={This paper proposes a method to exchange information among multiple swarms in particle swarm optimization. The provided algorithm is developed to solve problems that have landscapes with a high number of local optima. Each swarm provides two sets of .....} } @inproceedings{ieeebib71, title={ A Hybrid Optimization Algorithm based on Clonal Selection Principle and Particle Swarm Intelligence}, author = {Qiaoling Wang and Changhong Wang and X.Z. Gao}, booktitle={Sixth International Conference on Intelligent Systems Design and Applications, 2006. ISDA '06}, notes={Volume 2, Oct. 2006}, year={2006}, pages={975 - 979 }, abstract={This paperfirst discusses the background knowledge of the clonal selection algorithm and particle swarm method. The clonal selection algorithm is imitated by the basic principle of the adaptive immune response to virus stimulus. The particle swarm op..... } } @inproceedings{ieeebib710, title={ A Distributed Particle Swarm Optimization Algorithm for Swarm Robotic Applications}, author = {J.M. Hereford}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1678 - 1685 }, abstract={We have derived a version of the Particle Swarm Optimization algorithm that is suitable for a swarm consisting of a large number of small, mobile robots. The algorithm, called the distributed PSO (dPSO), is for  search type operations a.....} } @inproceedings{ieeebib711, title={ Determining RNA Secondary Structure using Set-based Particle Swarm Optimization}, author = {M. Neethling and A.P. Engelbrecht}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1670 - 1677 }, abstract={Determining RNA secondary structure computationally, rather than manually, has the advantage of being cheaper and quicker. This paper introduces a new Set-based Particle Swarm Optimization algorithm to optimize the structure of an RNA molecule, using.....} } @inproceedings{ieeebib712, title={ Optimal Parameter Selection in Image Similarity Evaluation Algorithms Using Particle Swarm Optimization}, author = {K. Kameyama and N. Oka and K. Toraichi}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1079 - 1086 }, abstract={Image relevance evaluation in conventional Content-Based Image Retrieval (CBIR) researches typically relied on a given criterion. However, it is important that this criterion can be changed according to the use of the image database. This work propos.....} } @inproceedings{ieeebib713, title={ An Investigation into Mutation Operators for Particle Swarm Optimization}, author = {P.S. Andrews}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1044 - 1051 }, abstract={The Particle Swarm Optimization (PSO) technique can be augmented with an additional mutation operator that helps prevent premature convergence on local optima. In this paper, different mutation operators for PSO are empirically investigated and compa.....} } @inproceedings{ieeebib714, title={ Particle Swarm Optimization Considering the Concept of Predator-Prey Behavior}, author = {M. Higashitani and A. Ishigame and K. Yasuda}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={434 - 437 }, abstract={Recently, a variety of optimization algorithms has developed as systems get complicated. One of those is called Particle Swarm Optimization (PSO). PSO is an algorithm which takes a cue from nature's bird flock or fish school and is known to have supe.....} } @inproceedings{ieeebib715, title={ Adding Local Search to Particle Swarm Optimization}, author = {S. Das and P. Koduru and Min Gui and M. Cochran and A. Wareing and S.M. Welch and B.R. Babin}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={428 - 433 }, abstract={Particle swarm optimization is a stochastic algorithm for optimizing continuous functions. It uses a population of particles that follow trajectories through the search space towards good optima. This paper proposes adding a local search component to.....} } @inproceedings{ieeebib716, title={ Particle Swarm Optimization for the Bi-objective Degree constrained Minimum Spanning Tree}, author = {E.F.G. Goldbarg and G.R. de Souza and M.C. Goldbarg}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={420 - 427 }, abstract={This paper presents a Particle Swarm Optimization algorithm for the multi-criteria degree constrained minimum spanning tree problem. The operators for the particles velocity are based upon local search and path-relinking procedures. The propos.....} } @inproceedings{ieeebib717, title={ A Particle Swarm Optimization Approach to A Multi-objective Reconfigurable Machine Tool Design Problem}, author = {Wei Liu and Ming Liang}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={2222 - 2229 }, abstract={The design of reconfigurable machine tools (RMTs) involves three criteria: configurability, cost and process accuracy with preferred priority order. This paper presents a modified fuzzy Chebyshev programming (MFCP) approach to achieving the best comp.....} } @inproceedings{ieeebib718, title={ Empirical Study of an Unconstrained Modified Particle Swarm Optimization}, author = {P.W. Moore and G.K. Venayagamoorthy}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1477 - 1482 }, abstract={In this paper, an unconstrained modified particle swarm optimization (UMPSO) algorithm is introduced and studied empirically. Four well known benchmark functions, with asymmetric initial position values, are used as testing functions for the UMPSO al.....} } @inproceedings{ieeebib719, title={ An Empirical Study on the Settings of Control Coefficients in Particle Swarm Optimization}, author = {N.M. Kwok and D.K. Liu and K.C. Tan and Q.P. Ha}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={823 - 830 }, abstract={The effects of randomness of control coefficients in Particle Swarm Optimization (PSO) are investigated through empirical studies. The PSO is viewed as a method to solve a coverage problem in the solution space when the global-best particle is report.....} } @inproceedings{ieeebib72, title={ A Novel Binary Particle Swarm Optimization Method Using Artificial Immune System}, author = {F. Afshinmanesh and A. Marandi and A. Rahimi-Kian}, booktitle={he International Conference on Computer as a Tool, 2005. EUROCON 2005}, notes={Volume 1, 2005}, year={2005}, pages={217 - 220 }, abstract={Particle Swarm Optimization, a nature-inspired evolutionary algorithm, has been successful in solving a wide range of real-value optimization problems. However, little attempts have been made to extend it to discrete problems. In this paper, a new bi..... } } @inproceedings{ieeebib720, title={ On Solving Multiobjective Bin Packing Problems Using Particle Swarm Optimization}, author = {D.S. Liu and K.C. Tan and C.K. Goh and W.K. Ho}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={2095 - 2102 }, abstract={The bin packing problem is widely found in applications such as loading of tractor trailer trucks, cargo airplanes and ships, where a balanced load provides better fuel efficiency and safer ride. In these applications, there are often conflicting cri.....} } @inproceedings{ieeebib721, title={ The Lévy Particle Swarm}, author = {T.J. Richer and T.M. Blackwell}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={808 - 815 }, abstract={Many foragers and wandering animals have been shown to follow a Lévy distribution of steps and it is conjectured here that this distribution may be useful for optimization algorithms too. This paper investigates the effectiveness of replacing th.....} } @inproceedings{ieeebib722, title={ Modeling MIDI Music as Multivariate Time Series}, author = {A. Kalos}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={2058 - 2064 }, abstract={A method of modeling music using multivariate time series models is described. The models are generated using a hybrid neural networks/discrete particle swarm optimization technique. Such models capture the essence of a piece of music, capable of gen.....} } @inproceedings{ieeebib723, title={ PSO-E: Particle Swarm with Exponential Distribution}, author = {R.A. Krohling and L. dos Santos Coelho}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1428 - 1433 }, abstract={Studies with the Gaussian and Cauchy probability distributions have shown that the performance of the standard PSO algorithm can be improved. But these versions may also get stuck in local minima when optimizing functions with many local minima in hi.....} } @inproceedings{ieeebib724, title={ A Discrete Particle Swarm Optimization Algorithm for Single Machine Total Earliness and Tardiness Problem with a Common Due Date}, author = {Quan-Ke Pan and M.F. Tasgetiren and Yun-Chia Liang}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={3281 - 3288 }, abstract={In this paper, a discrete particle swarm optimization (DPSO) algorithm is presented to solve the single machine total earliness and tardiness penalties with a common due date. A modified version of HRM heuristic presented by Hino et al. in [7], here .....} } @inproceedings{ieeebib725, title={ Comparing Particle Swarm Optimisation and Genetic Algorithms for Nonlinear Mapping}, author = {A. Edwards and A.P. Engelbrecht}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={694 - 701 }, abstract={Reducing the dimensionality of high-dimensional data simplifies how data is presented, allowing easier visualisation of high-dimensional data and facilitating more efficient extraction of knowledge. Nonlinear mapping methods transform data existing i.....} } @inproceedings{ieeebib726, title={ Cryptanalysis of Simple Substitution Ciphers Using Particle Swarm Optimization}, author = {M.F. Uddin and A.M. Youssef}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={677 - 680 }, abstract={We investigate the use of Particle Swarm Optimization (PSO) in automated cryptanalysis of classical simple substitution ciphers. Based on our experimental results, PSO-based attacks proved to be very effective on various sets of encoding keys......} } @inproceedings{ieeebib727, title={ Boolean Particle Swarm Optimization and Its Application to the Design of a Dual-Band Dual-Polarized Planar Antenna}, author = {A. Marandi and F. Afshinmanesh and M. Shahabadi and F. Bahrami}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={3212 - 3218 }, abstract={Particle Swarm Optimization (PSO) is a powerful evolutionary computation technique for solving continuous-valued optimization problems in various fields of engineering. However, its binary version could not attract much attention such that research o.....} } @inproceedings{ieeebib728, title={ The Particle Swarm Interval Rule Optimizer with an Application to Drug Design Data}, author = {J. Paetz}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={2556 - 2562 }, abstract={Life sciences have become a wide area for applications of informatics. One prominent topic in life sciences is the design of new drugs. Chemists use combinatorial libraries for creating new molecules in laboratory, but the challenge is to find approp.....} } @inproceedings{ieeebib729, title={ Bilevel Optimization of Multi-Component Chemical Systems Using Particle Swarm Optimization}, author = {W. Halter and S. Mostaghim}, booktitle={IEEE Congress on Evolutionary Computation, 2006. CEC 2006.}, notes={16-21 July 2006}, year={2006}, pages={1240 - 1247 }, abstract={In this paper we study a real-world optimization problem in mineralogy which contains a large number of parameters and several objective functions. The problem has been described through a thermodynamic model for which the parameters have to be quant.....} } @inproceedings{ieeebib73, title={ Particle Swarm and Quantum Particle Swarm Optimization Applied to DS/CDMA Multiuser Detection in Flat Rayleigh Channels}, author = {L.D. de Oliveira and F. Ciriaco and T. Abrao and P.J.E. Jeszensky}, booktitle={2006 IEEE Ninth International Symposium on Spread Spectrum Techniques and Applications}, notes={Aug. 2006}, year={2006}, pages={133 - 137 }, abstract={The particle swarm and quantum particle swarm optimization (PSO and QPSO) techniques applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA) with multiuser detection (MuD) are analyzed, evaluated and compared. The swarm techniques ..... } } @inproceedings{ieeebib730, title={ A study of fitness inheritance and approximation techniques for multi-objective particle swarm optimization}, author = {M. Reyes-Sierra and C.A.C. Coello}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 1, 2-5 Sept. 2005}, pages={65 - 72 Vol.1 }, abstract={In this paper, we study the use of fitness inheritance and approximation techniques to reduce the number of fitness evaluations into a PSO-based multi-objective algorithm previously proposed by the authors. Fifteen fitness inheritance techniques and .....} } @inproceedings{ieeebib731, title={ Research on the Application of the Case Library Based on Grid Using Particle Swarm Optimization}, author = {Hong Zhu and Demin Wang and Wengang Zhou and Xin Liu and Ping Hu}, booktitle={2006. ICNSC '06. Proceedings of the 2006 IEEE International Conference on Networking, Sensing and Control}, notes={23-25 April 2006}, year={2006}, pages={681 - 685}, abstract={The application of case libraries has become a main problem in engineering designs. This paper presents an organizing scheme structured in catalogs and archives to design auto-body panel die-design case library. Meanwhile, we have developed a case li.....} } @inproceedings{ieeebib732, title={ A new kind of fuzzy particle swarm optimization FUZZY/spl I.bar/PSO algorithm}, author = {Bo Wang and GuoQiang Liang and ChanLin Wang and YunLong Dong}, booktitle={1st International Symposium on Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006}, notes={19-21 Jan. 2006}, year={2006}, pages={3 pp. }, abstract={The important condition of fully utilizing the PSO algorithm is to keep the harmony between searching in detail and exploring a new area. In this paper, based on the fuzzy set theory and the relation between individual and colony, a fuzzy control var.....} } @inproceedings{ieeebib733, title={ Research on method of the fault diagnosis for digital circuits}, author = {Yanli Hou and Chunhui Zhao and Yanping Liao and Shujin Pu}, booktitle={1st International Symposium on Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006}, notes={19-21 Jan. 2006}, year={2006}, pages={4 pp. }, abstract={Efficient diagnosis of faults in digital circuits requires high quality diagnostic test sets that are generated by effective algorithm. In this work, novel optimization algorithms for diagnostic test generation are proposed that require significantly.....} } @inproceedings{ieeebib734, title={ A 20 GHz compact scalable model of silicon-based on-chip spiral inductor for RFICS}, author = {S.K. Mandal and A. De}, booktitle={Microwave \& Telecommunication Technology, 2005 15th International Crimean Conference}, notes={Volume 2, 12-16 Oct. 2005}, year={2005}, pages={543 - 546 Vol. 2 }, abstract={In this paper, a new scalable compact high-frequency Si-based on-chip spiral inductor model is presented that consists of a new substrate network and underpass oxide leakage component to model the reduction in equivalent series resistance at higher f.....} } @inproceedings{ieeebib735, title={ Focusing ISAR images using the AJTF optimized with the GA and the PSO algorithm-comparison and results}, author = {W. Brinkman and Thayananthan Thayaparan}, booktitle={2006 IEEE Conference on Radar}, note={24-27 April 2006}, year={2006}, pages={8 pp. }, abstract={Algorithms based on the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm were designed for focusing inverse synthetic aperture radar (ISAR) images that suffered from degradation due to Doppler smearing. These algorithms opti.....} } @inproceedings{ieeebib736, title={ Prediction of the flow stress for 30 MnSi steel using evolutionary least squares support vector machine and mathematical models}, author = {Ai-ling Chen and Mu-lan Wang and Kun Liu}, booktitle={2005. ICIT 2005. IEEE International Conference on Industrial Technology}, notes={14-17 Dec. 2005}, year={2005}, pages={963 - 968}, abstract={To obtain the flow stress data under varying conditions of strain, strain rate and temperature, hot compression experiments are conducted on 30 MnSi steel specimens using a GLEEBLE 1500 thermal simulator. To more accurately predict flow stress, ELS-S.....} } @inproceedings{ieeebib737, title={ Velocity relaxed swarm intelligent tuning of fuzzy based power system stabilizer}, author = {V. Mukherjee and S.P. Ghoshal}, booktitle={Power India Conference, 2006 IEEE}, notes={10-12 April 2006}, year={2006}, pages={8 pp. }, abstract={This paper presents a novel velocity relaxed swarm intelligent approach for tuning of a dual input power system stabilizer (PSS) in a single machine infinite bus (SMIB) system. Velocity update relaxation particle swarm optimization (VURPSO) and binar.....} } @inproceedings{ieeebib738, title={ An improved model for optimal under voltage load shedding: particle swarm approach}, author = {T. Amraee and B. Mozafari and A.M. Ranjbar}, booktitle={Power India Conference, 2006 IEEE}, notes={10-12 April 2006}, year={2006}, pages={6 pp. }, abstract={Under voltage load shedding is one of the most important tools to avoid voltage instability. In this paper an optimal load shedding algorithm is developed. This approach is based on the concept of the static voltage stability margin and its sensitivi.....} } @inproceedings{ieeebib739, title={ Engine data classification with simultaneous recurrent network using a hybrid PSO-EA algorithm}, author = {Xindi Cai and D.C., II Wunsch}, booktitle={2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05. Proceedings}, notes={Volume 4, 31 July-4 Aug. 2005}, year={2005}, pages={2319 - 2323 vol. 4 }, abstract={We applied an architecture which automates the design of simultaneous recurrent network (SRN) using a new evolutionary learning algorithm. This new evolutionary learning algorithm is based on a hybrid of particle swarm optimization (PSO) and evolutio.....} } @inproceedings{ieeebib74, title={ A Hybrid Discrete Particle Swarm Optimization Algorithm to Solve Flow Shop Scheduling Problems}, author = {S. Chandrasekaran and S.G. Ponnambalam and R.K. Suresh and N. Vijayakumar}, booktitle={2006 IEEE Conference on Cybernetics and Intelligent Systems}, note={June 2006}, year={2006}, pages={1 - 6 }, abstract={This paper presents a method of applying particle swarm optimization (PSO) algorithm to a flow shop scheduling problem. Permutation encoding of job indices is used to represent particles. One particle of the initial swarm is generated using NEH heuri..... } } @inproceedings{ieeebib740, title={ Using Hardware-Based Particle Swarm Method for Dynamic Optimization of Adaptive Array Antennas}, author = {G. Kokai and T. Christ and H.H. Frhauf}, booktitle={First NASA/ESA Conference on Adaptive Hardware and Systems, 2006. AHS 2006}, notes={15-18 June 2006}, year={2006}, pages={51 - 58 }, abstract={The following article describes and discusses the suitability of the particle swarm optimization (PSO) for the employment with blind adaptation of the directional characteristic of array antennas. By means of extensive simulations it was confirmed th.....} } @inproceedings{ieeebib741, title={ Particle Swarm Optimization with Discrete Recombination: An Online Optimizer for Evolvable Hardware}, author = {J. Pena and A. Upegui and E. Sanchez}, booktitle={First NASA/ESA Conference on Adaptive Hardware and Systems, 2006. AHS 2006}, notes={15-18 June 2006}, year={2006}, pages={163 - 170 }, abstract={Self-reconfigurable adaptive systems have the possibility of adapting their own hardware configuration. This feature provides enhanced performance and flexibility, reflected in computational cost reductions. Self-reconfigurable adaptation requires po.....} } @inproceedings{ieeebib742, title={ Distributed odor source localization in dynamic environment}, author = {W. Jatmiko and Y. Ikemoto and T. Matsuno and T. Fukuda and K. Sekiyama}, booktitle={Sensors, 2005 IEEE}, notes={30 Oct.-3 Nov. 2005}, year={2005}, pages={4 pp. }, abstract={This paper addresses the problem of odor source localization in a dynamic environment, which means the odor distribution is changing over time. Modification particle swarm optimization is a well-known algorithm, which can continuously track a changin.....} } @inproceedings{ieeebib743, title={ Particle Swarm Optimization based PI controller tuning for Fermentation Process}, author = {K. Valarmathi and D. Devaraj and T.K. Radhakrishnan}, booktitle={International Conference on Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce}, notes={Volume 2, 28-30 Nov. 2005}, year={2005}, pages={1043 - 1048 }, abstract={The activities related to Fermentation process are uncertain and nonlinear in nature. It poses many challenging characteristics like multivariable interactions, unmeasured state variables, system and time varying parameters. Generally, PID controller.....} } @inproceedings{ieeebib744, title={ Determination of wavelet denoising threshold by PSO and GA}, author = {Mingyan Jiang and Dongfeng Yuan and Zheng Jiang and Miaomiao Wei}, booktitle={IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2005. MAPE 2005}, notes={Volume 2, 8-12 Aug. 2005}, year={2005}, pages={1426 - 1429 Vol. 2 }, abstract={In this paper, we drive the wavelet threshold error function, adopt the particle swarm optimization (PSO) and genetic algorithm (GA) to determine the optimal wavelet denoising threshold, the results show that our methods have better performance in si.....} } @inproceedings{ieeebib745, title={ Optimal control parameters for a UPFC in a multimachine using PSO}, author = {G.K. Venayagamoorthy}, booktitle={Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, 2005}, notes={6-10 Nov. 2005}, year={2005}, pages={6 pp. }, abstract={The crucial factor affecting the modern power systems today is load flow control. The unified power flow controller (UPFC) is an effective means for controlling the power flow and can provide damping capability during transient conditions. The UPFC i.....} } @inproceedings{ieeebib746, title={ Evolving agents in a market simulation platform - a test for distinct meta-heuristics}, author = {Naing Win Oo and V. Miranda}, booktitle={Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, 2005}, notes={6-10 Nov. 2005}, year={2005}, pages={6 pp. }, abstract={This paper presents a comparison in performance of 3 variants of genetic algorithms (GA) vs. 2 variants of evolutionary particle swarm optimization (EPSO), made in the extremely complex context of a multi-energy market simulation where the behavior o.....} } @inproceedings{ieeebib747, title={ Comparison of two metaheuristics with mathematical programming methods for the solution of OPF}, author = {P.N. Biskas and N.P. Ziogos and A. Tellidou and C.E. Zoumas and A.G. Bakirtzis and V. Petridis and A. Tsakoumis}, booktitle={Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, 2005}, notes={6-10 Nov. 2005}, year={2005}, pages={6 pp. }, abstract={This paper presents a comparison of different optimization methods developed for the solution of the nonlinear OPF problem with both continuous and discrete variables. Two mathematical programming methods are compared with two metaheuristics, a parti.....} } @inproceedings{ieeebib748, title={ PSO-based evolutionary optimization for black-box modeling of arbitrary shaped on-chip RF inductors}, author = {R. Bhattacharya and A. Joshi and T.K. Bhattacharya}, booktitle={2006 Topical Meeting on Silicon Monolithic Integrated Circuits in RF Systems, 2006. Digest of Papers}, notes={18-20 Jan. 2006}, year={2006}, pages={4 pp. }, abstract={In the present work a particle swarm optimization (PSO) based off-line system identification algorithm has been proposed for modeling of RF on-chip inductors. The proposed scheme has a distinctive feature that the determination of the system structur.....} } @inproceedings{ieeebib749, title={ A wide-band lumped element compact CAD model of Si-based planar spiral inductor for RFIC design}, author = {S.K. Mandal and A. De and A. Patra and S. Sural}, booktitle={19th International Conference on VLSI Design, 2006. Held jointly with 5th International Conference on Embedded Systems and Design.}, notes={3-7 Jan. 2006}, year={2006}, pages={6 pp. }, abstract={In this paper, a new lumped element compact Si-based on-chip spiral inductor model is presented for wide-band application. It consists of a new substrate network and underpass oxide leakage component to model the reduction in equivalent series resist.....} } @inproceedings{ieeebib75, title={ Lotto-Type Competitive Learning with Particle Swarm Features II}, author = {A. Luk and S. Lien}, booktitle={International Joint Conference on Neural Networks, 2006. IJCNN '06}, notes={16-21 July 2006}, year={2006}, pages={3640 - 3647 }, abstract={This correspondence describes our attempts of incorporating particle swarm features into competitive learning. We first outline our reinterpretation of the symbols and notations used in particle swarm optimisation (PSO) algorithms. Three versions of ..... } } @inproceedings{ieeebib750, title={ PSO-based learning rate adjustment for blind source separation}, author = {Chun-Ling Lin and Sheng-Ta Hsieh and tsung-Ying Sun and Chan-Cheng Liu}, booktitle={Proceedings of 2005 International Symposium on Intelligent Signal Processing and Communication Systems, 2005. ISPACS 2005}, notes={13-16 Dec. 2005}, year={2005}, pages={181 - 184 }, abstract={Blind source separation (BSS) is a technique for recovering a set of source signals without a priori information on the transformation matrix or the probability distributions of the source signals. In the previous works of BSS, the choice of the lear.....} } @inproceedings{ieeebib751, title={ Auto cropping for digital photographs}, author = {Mingju Zhang and Lei Zhang and Yanfeng Sun and Lin Feng and Weiying Ma}, booktitle={2005. ICME 2005. IEEE International Conference on Multimedia and Expo}, notes={6-8 July 2005}, year={2005}, pages={4 pp.}, abstract={In this paper, we propose an effective approach to the nearly untouched problem, still photograph auto cropping, which is one of the important features to automatically enhance photographs. To obtain an optimal result, we first formulate auto croppin.....} } @inproceedings{ieeebib752, title={ Improved Maximum Likelihood Estimation of Target Position in Wireless Sensor Networks using Particle Swarm Optimization}, author = {M.M. Noel and P.P. Joshi and T.C. Jannett}, booktitle={Third International Conference on Information Technology: New Generations, 2006. ITNG 2006}, notes={10-12 April 2006}, year={2006}, pages={274 - 279 }, abstract={Estimation of target position from multi-frame binary data provided by a wireless sensor network (WSN) can be done by optimizing a complex multimodal likelihood function. Deterministic quasi Newton- Raphson (QNR) schemes with line search are typicall.....} } @inproceedings{ieeebib753, title={ Design of a conformal microstrip antenna array mounted on an irregular dielectric surface}, author = {Xu-feng Liu and Yong-chang Jiao and Fu-shun Zhang and Yi-bo Chen}, booktitle={Microwave Conference Proceedings, 2005. APMC 2005. Asia-Pacific Conference Proceedings}, notes={Volume 3, 4-7 Dec. 2005}, year={2005}, pages={3 pp. }, abstract={A conformal microstrip antenna array mounted on a finite irregular dielectric surface is developed in this paper. In order to take into account the effects of the irregular dielectric surface, the VSWR and the radiation patterns of a single antenna e.....} } @inproceedings{ieeebib754, title={ Miniaturization of planar microwave filters with irregular geometries}, author = {Wen Wang and Yilong Lu and J.S. Fu}, booktitle={2005 IEEE International Workshop on Radio-Frequency Integration Technology: Integrated Circuits for Wideband Communication and Wireless Sensor Networks, 2005. Proceedings}, notes={30 Nov.-2 Dec. 2005}, year={2005}, pages={198 - 201 }, abstract={Traditional planar microwave filter designs are limited to regular shapes so that the results may not be optimal. In this paper, we present a novel design approach of planar microwave filters with irregular shapes, which leads to more freedom and pos.....} } @inproceedings{ieeebib755, title={ Gene Expression Data for DLBCL Cancer Survival Prediction with A Combination of Machine Learning Technologies}, author = {Rui Xu and Xindi Cai and D.C. Wunsch}, booktitle={Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the}, notes={01-04 Sept. 2005}, year={2005}, pages={894 - 897 }, abstract={Gene expression profiles have become an important and promising way for cancer prognosis and treatment. In addition to their application in cancer class prediction and discovery, gene expression data can be used for the prediction of patient survival.....} } @inproceedings{ieeebib756, title={ Particle evolutionary swarm optimization algorithm (PESO)}, author = {A.E.M. Zavala and A.H. Aguirre and E.R.V. Diharce}, booktitle={Sixth Mexican International Conference on Computer Science, 2005. ENC 2005}, notes={26-30 Sept. 2005}, year={2005}, pages={282 - 289 }, abstract={We introduce the PESO (particle evolutionary swarm optimization) algorithm for solving single objective constrained optimization problems. PESO algorithm proposes two new perturbation operators: "c-perturbation" and "m-perturbation". The goal of thes.....} } @inproceedings{ieeebib757, title={ PSO based bit rate optimization for MPEG-1/2 video coding}, author = {H.K. Arachchi and W.A.C. Fernando}, booktitle={2005. ICIP 2005. IEEE International Conference on Image Processing}, notes={Volume 2, 11-14 Sept. 2005}, year={2005}, pages={II - 329-32}, abstract={One of the significant problems in video compression schemes is the high fluctuation in output data rate over the video sequence. These compression schemes, in general, utilize a rate control algorithm in order to maintain the output data rate at a c.....} } @inproceedings{ieeebib758, title={ Using PSO algorithm to evolve an optimum input subset for a SVM in time series forecasting}, author = {Chunkai Zhang and Hong Hu}, booktitle={2005 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 4, 10-12 Oct. 2005}, year={2005}, pages={3793 - 3796 Vol. 4}, abstract={Using particle swarm optimization (PSO) algorithm to evolve an optimum input subset for a SVM is proposed Binary PSO algorithm is employed in feature selection, in which each particle represented as a binary vector corresponds to a candidate input su.....} } @inproceedings{ieeebib759, title={ Optimization of irregular LDPC codes on Rician channel}, author = {Xu Hua and Xu Cheng-qi and Zheng Xiao-chuan}, booktitle={2005 International Conference on Wireless Communications, Networking and Mobile Computing, 2005. Proceedings}, notes={Volume 1, 23-26 Sept. 2005}, year={2005}, pages={381 - 383 }, abstract={For irregular LDPC codes,the density evolution method can track the messages to find out the noise threshold, enabling optimization of the degree distribution. A new optimized scheme for irregular LDPC codes is proposed in this paper, which is combin.....} } @inproceedings{ieeebib76, title={ Analysis of Adaptive IIR Filter Design Based on Quantum-behaved Particle Swarm Optimization}, author = {Wei Fang and Jun Sun and Wenbo Xu}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3396 - 3400 }, abstract={Adaptive infinite impulse response (IIR) filters have a wide range of applications such as channel equation, echo canceling and system identification. As the error surface of IIR filters is usually multi-modal, it is necessary to use global optimizat..... } } @inproceedings{ieeebib760, title={ An evolved Seega player capable of strong novice-level play}, author = {A.M. Abdelbar and O. Soliman and S. Kinawy and H. Sayed}, booktitle={2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05. Proceedings}, notes={Volume 1, 31 July-4 Aug. 2005}, year={2005}, pages={332 - 336 vol. 1 }, abstract={Seega is an ancient Egyptian two-stage board game that, in certain aspects, is more difficult than chess. The two-player game is most commonly played on a 7 /spl times/ 7 board, but is also sometimes played on a 5 /spl times/ 5 or 9 /spl times/ 9 boa.....} } @inproceedings{ieeebib761, title={ Gene regulatory networks inference with recurrent neural network models}, author = {Rui Xu and D.C., II Wunsch}, booktitle={2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05. Proceedings}, notes={Volume 1, 31 July-4 Aug. 2005}, year={2005}, pages={286 - 291 vol. 1 }, abstract={Large-scale time series gene expression data generated from DNA microarray experiments provide us a new means to reveal fundamental cellular processes, investigate functions of genes, and understand their relations and interactions. To infer gene reg.....} } @inproceedings{ieeebib762, title={ Low complexity iris recognition based on wavelet probabilistic neural networks}, author = {Ching-Han Chen and Chia-Te Chu}, booktitle={2005 IEEE International Joint Conference on Neural Networks, 2005. IJCNN '05. Proceedings}, notes={Volume 3, 31 July-4 Aug. 2005}, year={2005}, pages={1930 - 1935 vol. 3 }, abstract={In this paper, a new technique is proposed for high efficiency iris recognition, which adopts Sobel transform and vertical projection to extract iris texture feature and wavelet probabilistic neural network (WPNN) as iris biometric classifier. The WP.....} } @inproceedings{ieeebib763, title={ Particle Swarm Optimisers for Cluster formation in Wireless Sensor Networks}, author = {S.M. Guru and S.K. Halgamuge and S. Fernando}, booktitle={Proceedings of the 2005 International Conference on Intelligent Sensors, Sensor Networks and Information Processing Conference, 2005}, notes={5-8 Dec. 2005}, year={2005}, pages={319 - 324 }, abstract={We describe the results of a performance evaluation of four extensions of Particle Swarm Optimisation (PSO) to reduce energy consumption in wireless sensor networks. Communication distances are an important factor to be reduced in sensor networks. By.....} } @inproceedings{ieeebib764, title={ Modeling Transcriptional Regulation in Chondrogenesis Using Particle Swarm Optimization}, author = {Yunlong Liu and H. Yokota}, booktitle={Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2005. CIBCB '05}, notes={14-15 Nov. 2005}, year={2005}, pages={1 - 7 }, abstract={Chondrogenesis is a complex developmental process involving many transcription factors. Using mRNA expression data and regulatory DNA sequences, we formulated a quantitative model to predict a set of transcription-factor binding motifs (TFBMs) as a c.....} } @inproceedings{ieeebib765, title={ Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization}, author = {E.K. Tang and P.N. Suganthan and X. Yao}, booktitle={Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2005. CIBCB '05}, notes={14-15 Nov. 2005}, year={2005}, pages={1 - 8 }, abstract={Feature selection is an important preprocessing technique for many pattern recognition problems. When the number of features is very large while the number of samples is relatively small as in the micro-array data analysis, feature selection is even .....} } @inproceedings{ieeebib766, title={ Cluster Based Congestion Management in Deregulated Electricity Market Using PSO}, author = {T. Meena and K. Selvi}, booktitle={INDICON, 2005 Annual IEEE}, notes={11-13 Dec. 2005}, year={2005}, pages={627 - 630 }, abstract={In this Paper, a Cluster based congestion management has been presented. The Paper is concerned with the Real and Reactive power rescheduling problem in a deregulated market environment. The aim of the proposed work is to minimize deviations from tra.....} } @inproceedings{ieeebib767, title={ An evolved recurrent neural network and its application in the state estimation of the CSTR system}, author = {Chunkai Zhang and Hong Hu}, booktitle={2005 IEEE International Conference on Systems, Man and Cybernetics}, notes={Volume 3, 10-12 Oct. 2005}, year={2005}, pages={2139 - 2143 Vol. 3}, abstract={Continuous stirred tank reactor system (CSTR) is a typical chemical reactor system with a complex nonlinear dynamic characteristics. In this paper, a recurrent neural network (RNN) evolved by a cooperative scheme is proposed to estimate the state of .....} } @inproceedings{ieeebib768, title={ Evolutionary Solo Pong players}, author = {W.B. Langdon and R. Poll}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 3, 2-5 Sept. 2005}, pages={2621 - 2628 Vol. 3 }, abstract={An Internet Java Applet http://www.cs.essex.ac.uk/staff/poli/SoloPong/ allows users anywhere to play the Solo Pong game. We compare people's performance to a hand coded "optimal" player and programs automatically produced by computational intelligenc.....} } @inproceedings{ieeebib769, title={ Tree swarm optimization: an approach to PSO-based tree discovery}, author = {C. Veenhuis and M. Koppen and J. Kruger and B. Nickolay}, booktitle={IEEE Congress on Evolutionary Computation, 2005. The 2005}, year={2005}, notes={Volume 2, 2-5 Sept. 2005}, pages={1238 - 1245 Vol. 2 }, abstract={In recent years a swarm-based optimization methodology called particle swarm optimization (PSO) has developed. PSO is highly explorative and primarily used in function optimization. This paper proposes a swarm-based learning algorithm based on PSO wh.....} } @inproceedings{ieeebib77, title={ Optimal Coalition Structure Based on Particle Swarm Optimization Algorithm in Multi-Agent System}, author = {Yan Shen and Bing Guo and Dianhui Wang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={2494 - 2497 }, abstract={Coalition is an important way of cooperation for multi-Agent system. To maximize the summation of the coalition values, and to search for an optimized coalition structure in a minimal searching range, a coalition structure optimization algorithm in m..... } } @inproceedings{ieeebib770, title={ Competitive approaches to PSO algorithms via new acceleration co-efficient variant with mutation operators}, author = {M. Senthil Arumugam and A. Chandramohan and M.V.C. Rao}, booktitle={Sixth International Conference on Computational Intelligence and Multimedia Applications, 2005}, notes={16-18 Aug. 2005}, year={2005}, pages={225 - 230 }, abstract={This paper presents a few new competitive approaches to particle swarm optimization (PSO) algorithm in terms of the global and local best values (GLbest-PSO) and the standard PSO along with three set of variants namely, inertia weight (IW), accelerat.....} } @inproceedings{ieeebib771, title={ Understanding particle swarm optimisation by evolving problem landscapes}, author = {W.B. Langdon and R. Poll and O. Holland and T. Krink}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={30 - 37}, abstract={Genetic programming (GP) is used to create fitness landscapes, which highlight strengths, and weaknesses of different types of PSO and to contrast population-based swarm approaches with non stochastic gradient followers (i.e. hill climbers). These au.....} } @inproceedings{ieeebib772, title={ A comparison of PSO and backpropagation for training RBF neural networks for identification of a power system with STATCOM}, author = {S. Mohaghegi and Y. del Valle and G.K. Venayagamoorthy and R.G. Harley}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={381 - 384}, abstract={Backpropagation algorithm is the most commonly used algorithm for training artificial neural networks. While being a straightforward procedure, it suffers from extensive computations, relatively slow convergence speed and possible divergence for cert.....} } @inproceedings{ieeebib773, title={ Cognitive swarms for rapid detection of objects and associations in visual imagery}, author = {Y. Owechko and S. Medasani}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={420 - 423}, abstract={We have developed a new optimization-based framework for computer vision that combines ideas from particle swarm optimization (PSO) and statistical pattern recognition to rapidly and accurately detect and classify objects in visual imagery. Swarm int.....} } @inproceedings{ieeebib774, title={ CiClops: computational intelligence collaborative laboratory of pantological software}, author = {E.S. Peer and A.P. Engelbrecht and G. Pampara and B.S. Masiye}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={130 - 137}, abstract={This paper presents CiClops, which is a virtual laboratory for performing experiments, using computational intelligence (CI) algorithms that scale over multiple workstations. Additionally, the paper introduces CIlib, which is an open source library o.....} } @inproceedings{ieeebib775, title={ Why does it need velocity?}, author = {J. Kennedy}, booktitle={Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.}, notes={8-10 June 2005}, year={2005}, pages={38 - 44}, abstract={The particle swarm algorithm differs from other EAs in its use of "velocity" - a particle tends to move in the same direction it moved on the previous iteration. This paper explores variations and dimensions of velocity in an effort to understand wha.....} } @inproceedings{ieeebib776, title={ Application of particle swarm optimization for microwave imaging of lossy dielectric objects}, author = {T. Huang and A.S. Mohan}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 1B, 3-8 July 2005}, year={2005}, pages={852 - 855 vol. 1B }, abstract={In this paper we have shown a novel microwave reconstruction technique using the PSO technique. Also a new damping boundary condition for the PSO technique is proposed. Our simulation results have shown the effectiveness of the proposed technique for.....} } @inproceedings{ieeebib777, title={ An efficiency-constrained application of a modified Bernstein polynomial for conformal array amplitude excitation optimization}, author = {D.W. Boeringer and D.H. Werner}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 1B, 3-8 July 2005}, year={2005}, pages={759 - 762 vol. 1B }, abstract={This paper starts by reviewing a generalized definition of aperture efficiency appropriate for conformal arrays with directional radiating elements. A modified Bernstein polynomial, defined with just five parameters, is introduced which provides a fl.....} } @inproceedings{ieeebib778, title={ A new hybrid evolutionary algorithm for high dimension electromagnetic problems}, author = {E.A. Grimaldi and A. Gandelli and F. Grimaccia and M. Mussetta and R.E. Zich}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 2A, 3-8 July 2005}, year={2005}, pages={61 - 64 vol. 2A }, abstract={In this paper the authors present a new hybrid evolutionary algorithm, particularly suitable for high dimension electromagnetic problems. This method, called GSO, genetical swarm optimization, essentially combines the features of other two well known.....} } @inproceedings{ieeebib779, title={ Investigation of the quantum particle swarm optimization technique for electromagnetic applications}, author = {S. Mikki and A.A. Kishk}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 2A, 3-8 July 2005}, year={2005}, pages={45 - 48 vol. 2A }, abstract={We introduce the QPSO into the electromagnetic community by illustrating its application to linear array antenna synthesis problems. A generalized framework that allows the user to derive several versions of the quantum method is proposed. Based on u.....} } @inproceedings{ieeebib78, title={ Tracking Changing Extrema with Modified Adaptive Particle Swarm Optimizer}, author = {Shimin Shan and Guishi Deng}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={3305 - 3309 }, abstract={The purpose of this paper is to present a modified PSO (Particle Swarm Optimization) algorithm applied to the complex dynamic environment. The algorithm presented is referred as Improved Adaptive Particle Swarm Optimizer (IAPSO). A new variable-"Acti..... } } @inproceedings{ieeebib780, title={ Design of E-shaped dual-band and wideband patch antennas using parallel PSO/FDTD algorithm}, author = {Nanbo Jin and Y. Rahmat-Samii}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 2A, 3-8 July 2005}, year={2005}, pages={37 - 40 vol. 2A }, abstract={The particle swarm optimization (PSO) technique is applied in this paper to the design of E-shaped patch antennas. Different fitness functions are utilized to denote different antenna performance, and a finite difference time domain (FDTD) analyzer e.....} } @inproceedings{ieeebib781, title={ Improved PSO algorithms for electromagnetic optimization}, author = {L. Matekovits and M. Mussetta and P. Pirinoli and S. Selleri and R.E. Zich}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 2A, 3-8 July 2005}, year={2005}, pages={33 - 36 vol. 2A }, abstract={Some variations over the basic particle swarm algorithm are here proposed, aimed at a more efficient search over the solution space and exhibiting a negligible overhead in complexity and speed. The proposed algorithms are then applied to the test cas.....} } @inproceedings{ieeebib782, title={ An integrated stochastic multi-scaling strategy for microwave imaging applications}, author = {D. Franceschini and A. Massa}, booktitle={Antennas and Propagation Society International Symposium, 2005 IEEE}, notes={Volume 1A, 3-8 July 2005}, year={2005}, pages={209 - 212 Vol. 1A }, abstract={This work presents an improved multi-scale algorithm for microwave imaging of two-dimensional scatterers. The proposed methodology includes a feedback between high-and low-resolution reconstructions in order to correlate the iterative reconstruction .....} } @inproceedings{ieeebib783, title={ Robust neural networks using motes}, author = {J.M. Hereford and T. Kuyucu}, booktitle={2005 NASA/DoD Conference on Evolvable Hardware, 2005. Proceedings}, notes={29 June-1 July 2005}, year={2005}, pages={117 - 124 }, abstract={The goal of this research is to derive circuits that can recover from component failure. Our approach is to replace a single monolithic computing element with a system of simple, redundant, interconnected processing nodes such as a neural net. Each n.....} } @inproceedings{ieeebib784, title={ Parallel PSO/FDTD algorithm for the optimization of patch antennas and EBG structures}, author = {Nanbo Jin and Y. Rahmat-Samii}, booktitle={IEEE/ACES International Conference on Wireless Communications and Applied Computational Electromagnetics, 2005}, notes={3-7 April 2005}, year={2005}, pages={582 - 585 }, abstract={A novel evolutionary optimization technique is presented in this paper by introducing its applications in some representative electromagnetic design problems. The kernel of the optimizer applies particle swarm optimization (PSO) algorithm, and the fi.....} } @inproceedings{ieeebib785, title={ An Improved PSO Approach for Profit-based Unit Commitment in Electricity Market}, author = {Yuan Xiaohui and Yuan Yanbin and Wang Cheng and Zhang Xiaopan}, booktitle={Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES}, notes={15-18 Aug. 2005}, year={2005}, pages={1 - 4 }, abstract={In this paper, we propose a formulation of the unit commitment problem based on the profit under the deregulated electricity market(PBUC). We express the unit commitment problem as a mixed integer nonlinear optimization problem in which the objective.....} } @inproceedings{ieeebib786, title={ Particle swam optimization for image registration}, author = {H. Talbi and M.C. Batouche}, booktitle={2004 International Conference on Information and Communication Technologies: From Theory to Applications, 2004. Proceedings}, notes={19-23 April 2004}, year={2004}, pages={397 - 398 }, abstract={This paper discusses the particle swam optimization for image registration. The term particle swarm optimization (PSO) refers to a relatively new family of algorithms that may be used to find optimal (or near optimal) solutions to numerical and quali.....} } @inproceedings{ieeebib787, title={ Photo Time-Stamp Recognition Based on Particle Swarm Optimization}, author = {Bao Fumin and Li Aiguo and Qin Zheng}, booktitle={IEEE/WIC/ACM International Conference on Web Intelligence, 2004. WI 2004. Proceedings}, notes={20-24 Sept. 2004}, year={2004}, pages={529 - 532 }, abstract={Time-stamp in image shows the time when an image was taken, and which is important information for retrieval. An automatic photo time-stamp recognition approach is proposed in this paper. The proposed method consists of three steps: 1) A photo is rou.....} } @article{ieeebibJ788, title={ Evolving Problems to Learn About Particle Swarm Optimizers and Other Search Algorithms}, author={W. B. Langdon and R. Poli}, journal={IEEE Transactions on Evolutionary Computation : Accepted for future publication}, volume= {PP}, issue= 99, date={ 2007}, pages={1 - 1 }, year={2007}, abstract={We use evolutionary computation (EC) to automatically find problems which demonstrate the strength and weaknesses of modern search heuristics. In particular, we analyze particle swarm optimization (PSO), differential evolution (DE), and covariance ma..... } } @article{ieeebibJ789, title={ Operating Schedule of Battery Energy Storage System in a Time-of-Use Rate Industrial User With Wind Turbine Generators: A Multipass Iteration Particle Swarm Optimization Approach}, author={Lee T.-Y. }, journal={IEEE Transactions on Energy Conversion : Accepted for future publication}, volume= {PP}, issue= 99, date={ 2007}, pages={1 - 1 }, year={2007}, abstract={This paper presents a new algorithm for the solution of nonlinear optimal scheduling problems. This algorithm is called multipass iteration particle swarm optimization (MIPSO). A new index called iteration best is incorpor..... } } @inproceedings{ieeebib79, title={ A Modified Particle Swarm Optimization Algorithm for Support Vector Machine Training}, author = {Hejin Yuan and Yanning Zhang and Dengfu Zhang and Gen Yang}, booktitle={The Sixth World Congress on Intelligent Control and Automation, 2006. WCICA 2006}, notes={Volume 1, 21-23 June 2006}, year={2006}, pages={4128 - 4132 }, abstract={A new modified particle swarm optimization algorithm for linear equation constrained optimization problem was put forward. And the method using this algorithm to train support vector machine was given. In the new algorithm, the particle studies not o..... } } @article{ieeebibJ790, title={ Self-Organizing and Self-Evolving Neurons: A New Neural Network for Optimization}, author={Sitao Wuand Tommy W. S. Chow}, journal={IEEE Transactions on Neural Networks}, volume= 18, issue= 2, date={ March 2007}, pages={385 - 396 }, year={2007}, abstract={A self-organizing and self-evolving agents (SOSENs) neural network is proposed. Each neuron of the SOSENs evolves itself with a simulated annealing (SA) algorithm. The self-evolving behavior of each neuron is a local improvement that results in speed.....} } @article{ieeebibJ791, title={ An Im