Hybrid Artificial Fish School Algorithm for Solving Ill-conditioned Linear Systems of Equations

摘要：

Based on particle swarm optimization (PSO) and artificial fish swarm algorithm (AFSA), a hybrid artificial fish swarm optimization algorithm is proposed. The novel method makes full use of the quickly local convergent performance of PSO and the global convergent performance of AFSA, and then is used for solving ill-conditioned linear systems of equations. Finally, the numerical experiment results show that the hybrid artificial fish swarm optimization algorithm owns a good globally convergent performance with a faster convergent rate. It is a new way for solving ill-conditioned linear systems of equations.

关键词： particle swarm optimization hybrid artificial fish swarm algorithm ill-conditioned linear systems of equations

作者: WEI Xiu-xi ZENG Hai-wen ZHOU Yong-quan

作者单位: Information Engineering Department Guangxi International Business Vocational College Nanning,530007, College of Computer and Information Science Guangxi University for nationalities Nanning, 530006, Ch

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 290-294

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）