粒子群算法(共107张PPT).pptxVIP

粒子群算法;;;Swarm Intelligence;Swarm Intelligence(续);Swarm Intelligence(续);Swarm Intelligence(续);Swarm Intelligence(续);Swarm Intelligence(续);Swarm Intelligence(续);Swarm Intelligence(续);Swarm Intelligence(续);蚁群算法;蚁群算法(续);蚁群算法(续);其它群智能优化算法;其它群智能优化算法（续）; 粒子群算法(particle swarm optimization，PSO)由Kennedy和Eberhart在1995年提出，该算法模拟鸟集群飞行觅食的行为，鸟之间通过集体的协作使群体达到最优目的，是一种基于Swarm Intelligence的优化方法。同遗传算法类似，也是一种基于群体叠代的，但并没有遗传算法用的交叉以及变异，而是粒子在解空间追随最优的粒子进行搜索。PSO的优势在于简单容易实现同时又有深刻的智能背景，既适合科学研究，又特别适合工程应用，并且没有许多参数需要调整。 ;James Kennedy received the Ph.D. degree from theUniversity of North Carolina, Chapel Hill, in 1992.He is with the U.S. Department of Labor, Washington,DC. He is a Social Psychologist who has been working with the particle swarm algorithm since 1994. He has published dozens of articles and chapters on particle swarms and related topics, in computer science and social science journals and proceedings. He is a coauthor of Swarm Intelligence (San Mateo, CA: Morgan Kaufmann, 2001), with R.C. Eberhart and Y. Shi, now in its third printing.;Russell C. Eberhart (M’88–SM’89–F’01) received the Ph.D. degree in electrical engineering from Kansas State University, Manhattan.He is the Chair and Professor of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University–Purdue University Indianapolis (IUPUI),Indianapolis, IN. He is coeditor of Neural Network PC Tools(1990),coauthor of Computational Intelligence PC Tools (1996), coauthor of Swarm Intelligence(2001), Computational Intelligence: Concepts to Implementations(2004). He has published over 120 technical papers.Dr. Eberhart was awarded the IEEE Third Millenium Medal. In 2002, he became a Fellow of the American Institute for Medical and Biological Engineering.;近年PSO方面文献的数量;PSO产生背景之一：复杂适应系统;复杂适应系统（CAS）续;PSO产生背景之二:人工生命 ;基本PSO算法 ;基本PSO算法（续）;基本PSO算法(续);基本PSO算法(续);基本PSO算法(续);基本PSO算法(续);PSO与EC的异同 ;PSO与EC的异同（续）;PSO与EC的异同（续）;PSO与EC的异同（续）;PSO与EC的异同（续）;Particle Swarm研究热点;粒子运动轨迹的分析 ;粒子运动轨迹的分析（续）;粒子运动轨迹的分析（续）;粒子