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题名:
An Enhanced Particle Swarm Optimization Algorithm
作者: Xue-yao Gao ; Li-quan Sun ; Da-song Sun
关键词: Particle swarm ; local extremum ; chaos search ; optimization algorithm
刊名: Information Technology Journal
发表日期: 2009
卷: 8, 期:8, 页:1263-1268
收录类别: 其他
合作性质: 其它
摘要: Particle Swarm Optimization (PSO) algorithm is often used for finding optimal solution, but it easily entraps into the local extremum in later evolution period. Based on improved chaos searching strategy, an enhanced particle swarm optimization algorithm is proposed in this study. When particles get into the local extremum, they are activated by chaos search strategy, where the chaos search area is controlled in the neighborhood of current optimal solution by reducing search area of variables. The new algorithm not only gets rid of the local extremum effectively but also enhances the precision of convergence significantly. Experiment results show that the proposed algorithm is better than standard PSO algorithm in both precision and stability.
语种: 中文
内容类型: 期刊论文
URI标识: http://ir.iscas.ac.cn/handle/311060/1340
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Xue-yao Gao,Li-quan Sun,Da-song Sun. An Enhanced Particle Swarm Optimization Algorithm[J]. Information Technology Journal,2009-01-01,8(8):1263-1268.
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