Hybrid Artificial Fish Swarm Algorithm for Solving Ill-Conditioned Linear Systems of Equations

被引:0
|
作者
Zhou, Yongquan [1 ]
Huang, Huajuan [1 ]
Zhang, Junli [1 ]
机构
[1] Guangxi Univ Nationalities, Coll Math & Comp Sci, Nanning 530006, Guangxi, Peoples R China
来源
关键词
Particle swarm optimization; hybrid artificial fish swarm Algorithm; ill-conditioned linear systems of equations;
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
Based on particle swarm optimization (PSO) and artificial fish swarm algorithm (AFSA), this paper proposes a hybrid artificial fish swarm algorithm (HAFSA). The method makes full use of the fast local convergence performance of PSO and the global convergence performance of AFSA, and then is used for solving ill-conditioned linear systems of equations. Finally, the numerical experiment results show that hybrid artificial fish swarm algorithm owns a better global convergence performance with a faster convergence rate. It is a new way to solve ill-conditioned linear systems of equations.
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页码:656 / 661
页数:6
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