• DocumentCode
    536317
  • 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
  • Volume
    1
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    290
  • Lastpage
    294
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-6582-8
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2010.5658678
  • Filename
    5658678