The Simulation and Improvement of Particle Swarm Optimization Based on Cellular Automata

被引：2
|
作者：
Yu Fengxia [1 ]
Li Gang [1 ]
机构：
[1] Ningbo Univ, Ningbo 315211, Zhejiang, Peoples R China
来源：
2012 INTERNATIONAL WORKSHOP ON INFORMATION AND ELECTRONICS ENGINEERING | 2012年 / 29卷
关键词：
Simulation; particle swarm optimization; cellular automata; prematurity detection;
D O I：
10.1016/j.proeng.2012.01.097
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
We observed that PSO algorithm was easily falling into local extreme point by using cellular automata simulation, and developed several improvement strategies which drew inspiration from simulation, such as adding additional particle into updated formula, introducing crossover operator and mutation disturbance when the premature convergence occurs. The experiments validated new algorithm on 10 benchmark functions, and results showed that the improved PSO algorithm has better stability and higher accuracy. (c) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Harbin University of Science and Technology
引用
收藏
页码：1113 / 1118
页数：6
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