Hybrid Particle Swarm Optimization Algorithm for Solving Systems of Nonlinear Equations

被引：25
|
作者：
Ouyang, Aijia [1 ]
Zhou, Yongquan [1 ]
Luo, Qifang [1 ]
机构：
[1] Guangxi Univ Nationalities, Coll Math & Comp Sci, Nanning 53006, Peoples R China
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING ( GRC 2009) | 2009年
关键词：
systems of nonlinear equations; simplex method; particle swarm optimization algorithm;
D O I：
10.1109/GRC.2009.5255079
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A hybrid particle swarm optimization (HPSO) algorithm, which combines the advantages of Nelder-Mead simplex method (SM) and particle swarm optimization (PSO) algorithm, is put forward to solve systems of nonlinear equations, and it can be used to overcome the difficulty in selecting good initial guess for SM and inaccuracy of PSO due to being easily trapped into local optimal. The algorithm has sufficiently displayed the performance of PSO's global searching and SM's accurate local search. Numerical computation results show that the approach has great robust, high convergence rate and precision, it can give satisfactory solutions of nonlinear equations.
引用
收藏
页码：460 / 465
页数：6
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