A Hybrid Particle Swarm Algorithm for Nonlinear Parameter Estimation

被引：0
|
作者：
Pei, Shengyu [1 ]
Zhou, Yongquan [1 ]
Luo, Qifang [1 ]
机构：
[1] Guangxi Univ Nationalities, Coll Math & Comp Sci, Nanning 530006, Peoples R China
来源：
ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL I, PROCEEDINGS | 2009年
关键词：
particle swarm optimization; parameters estimation; genetic algorithm; crossover operator;
D O I：
10.1109/ICICTA.2009.61
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A hybrid particle swarm optimization algorithm for solving non-linear parameter estimation is proposed, which is based on genetic algorithm. And can increase the diversity of population and make the particles have a definite evolution direction when they are renewed. This improved approach has been tested on some problems commonly used in this paper. The results show that the proposed approach is an efficient and can reach a higher precision.
引用
收藏
页码：219 / 222
页数：4
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