Gaussion mutation Particle Swarm Optimization with dynamic adaptation inertia weight

被引：3
|
作者：
Li, Lili [1 ]
He, Xingshi [1 ]
机构：
[1] Xian Polytech Univ, Dept Math, Xian, Peoples R China
来源：
2009 WRI WORLD CONGRESS ON SOFTWARE ENGINEERING, VOL 4, PROCEEDINGS | 2009年
关键词：
CONVERGENCE; ALGORITHM;
D O I：
10.1109/WCSE.2009.24
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
An improved PSO with decreasing inertia weight is proposed in this paper, which is different from the inertia weight of standard PSO. In addition, a new social component instead of the old one to make more explore and a tiny Gauss perturbation joined in the position equation to help maintain swarm diversity. Four standard test functions with asymmetric initial range settings are used to prove its validity. Experimental results verify its superiority both in convergent speed and solution precision. Conclusions are drawn in the end.
引用
收藏
页码：454 / 459
页数：6
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