A New Particle Swarm Optimization Algorithm and Its Numerical Analysis

被引：0

作者：

Gao, Yuelin ^{[1
]}

Lei, Fanfan ^{[1
]}

Wang, Miaomiao ^{[1
]}

机构：

[1] N Ethn Univ, Inst Informat & Syst Sci, Yinchuan 750021, Peoples R China

来源：

ADVANCES IN SWARM INTELLIGENCE, PT 1, PROCEEDINGS | 2010年 / 6145卷

关键词：

particle swarm optimization; velocity equation; numerical analysis;

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：

The speed equation of particle swarm optimization is improved by using a convex combination of the current best position of a particle and the current best position which the whole particle swarm as well as the current position of the particle, so as to enhance global search capability of basic particle swarm optimization. Thus a new particle swarm optimization algorithm is proposed. Numerical experiments show that its computing time is short and its global search capability is powerful as well as its computing accuracy is high in compared with the basic PSO.

引用

页码：60 / 67

页数：8

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