Title :
Hybrid artificial fish school algorithm for solving ill-conditioned linear systems of equations
Author :
Wei, Xiu-Xi ; Zeng, Hai-Wen ; Zhou, Yong-Quan
Author_Institution :
Inf. Eng. Dept., Guangxi Int. Bus. Vocational Coll., Nanning, China
Abstract :
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.
Keywords :
linear systems; particle swarm optimisation; artificial fish swarm algorithm; global convergent performance; hybrid artificial fish school algorithm; ill-conditioned linear equation system; local convergent performance; particle swarm optimization; Equations; Particle swarm optimization; hybrid artificial fish swarm algorithm; ill-conditioned linear systems of equations; particle swarm optimization;
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
DOI :
10.1109/ICICISYS.2010.5658678