• DocumentCode
    3300097
  • Title

    An Improved Gaussian Dynamic Particle Swarm Optimization Algorithm

  • Author

    Ni, Qingjian ; Xing, Hancheng

  • Author_Institution
    Coll. of Comput. Sci. & Eng., Southeast Univ., Nanjing
  • Volume
    1
  • fYear
    2006
  • fDate
    Nov. 2006
  • Firstpage
    316
  • Lastpage
    319
  • Abstract
    An improved Gaussian dynamic particle swarm optimization (PSO) algorithm is proposed in this paper. In the proposed version of PSO, the original swarm of particles is initialized by canonical PSO. The time varying linear inertial weight is reintroduced to add to the position update formula. And the crazinness variable is also used in order to maintain the diversity of particle swarms. The performance of improved Gaussian dynamic PSO is demonstrated by applying it to several benchmark functions and comparing to other variants of PSO
  • Keywords
    Gaussian processes; particle swarm optimisation; time-varying systems; Gaussian dynamic particle swarm optimization algorithm; time varying linear inertial weight; Benchmark testing; Birds; Computer science; Educational institutions; Equations; Evolutionary computation; Genetic algorithms; Marine animals; Particle swarm optimization; Space exploration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security, 2006 International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    1-4244-0605-6
  • Electronic_ISBN
    1-4244-0605-6
  • Type

    conf

  • DOI
    10.1109/ICCIAS.2006.294146
  • Filename
    4072099