Particle swarm optimization system algorithm

被引:0
|
作者
Cai, Manjun [1 ]
Zhang, Xuejian [1 ]
Tian, Guangjun [1 ]
Liu, Jincun [1 ]
机构
[1] YanShan Univ, Inst Elect Engn, Qinhuangdao 066004, Hebei, Peoples R China
关键词
evolutionary computation; Particle Swarm Optimization; new PSO system;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Particle Swarm Optimization algorithm (PSO) is a new evolutionary computation method, which has been successfully applied to many fields. However it also has problem of premature convergence and slow search speed. To deal with those problems we make some improvements on traditional PSO to make its search velocity quickly. Then we add some others algorithms and new ideas to PSO to construct a new PSO system (PSOS). Those algorithms and new ideas will be applied to one or several particles, which have their own specified duty or responsibility, and work in collaboration and communicate with others common particles in the PSOS. In the process of iterative computation, particles will keep updating their position according to specific circumstances until achieve their common purpose,that means finding out the global optimum solution quickly and exactly.
引用
收藏
页码:388 / +
页数:3
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