文件名称：A modified particle swarm optimization via particle visual modeling analysis
文件大小：788KB
文件格式：PDF
更新时间：2013-05-29 12:29:19
Particle swarm optimization Visual modeling
A particle is treated as a whole individual in all researches on particle swarm optimization (PSO) currently, these are not concerned with the information of every particle's dimensional vector. A visual modeling method describing particle's dimensional vector behavior is presented in this paper. Based on the analysis of visual modeling, the reason for premature convergence and diversity loss in PSO is explained, and a new modified algorithm is proposed to ensure the rational flight of every particle's dimensional component. Meanwhile, two parameters of particle-distribution-degree and particle- dimension-distance are introduced into the proposed algorithm in order to avoid premature convergence. Simulation results of the new PSO algorithm show that it has a better ability of finding the global optimum, and still keeps a rapid convergence as with the standard PSO.