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Home: Artificial Life: Particle Swarm: People
- Abido Mohammad
Assistant Professor, Department of electrical Engineering, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia. His research area includes Power System Analysis, Stability, and Control, Flexible AC Transmission Lines (FACTS), Power System Planning and Operation, Optimization Techniques, Evolutionary Algorithms,Neuro-Fuzzy Control and Hybrid Intelligent Systems,Reactive Power Control and Voltage Stability
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- Engelbrecht, Andries P.
Computational Intelligence Research Group, University of Pretoria. Research is done in theoretical aspects of PSO and developing new improved PSO models.
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- Fukuyama, Yoshikazu
His research interests include application of intelligent systems to power systems and power systems analysis. Some of his papers can be downloaded from the website.
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- Hu, Xiaohui
PhD student at Purdue University, research focus is biomedical data analysis and computational intelligence, especially particle swarm optimization.
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- Kennedy, James
One of the founders of particle swarm optimization. research psychologist at bureau of labor statistics
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- Lascari, Eleni
Eleni Lascari's Homepage, Personal information, scientific links, publications, game theory, particle swarm, stochastic optimization, evolutionary algorithms
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- Mohan, Chilukuri
Professor at Syracuse University, research interests include evolutionary algorithms and artificial neural networks.
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- Parsopoulos, Konstantinos
Ph.D. candidate, Department of Mathematics, University of Patras, Greece. CV, Publications, particle swarm, Parsopoulos
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- Shi, Yuhui
Researcher in Particle swarm optimization, fuzzy logic, evolutionary computation.
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- Sinclair, Mark C.
Research interests include telecommunications network design, evolutionary algorithms, bbject technology, software agents. you can find a java applet that shows how pso works.
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- van den Bergh, Frans
PhD Student at University of Pretoria, South Africa. He is working on some enhancements to the basic Particle Swarm Optimizer
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- Xie, Xiao-Feng
Evolutionary and learning algorithms, such as genetic algorithms (GAs), particle swarm optimization (PSO), differential evolution (DE), hybrid algorithms, etc., for nonlinear programming problems and the relations to self-organization of complex systems.
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