• DocumentCode
    2870012
  • Title

    The Research of the Niche Particle Swarm Optimization Based on Self-Adaptive Radius Technology

  • Author

    Zhao, Qingling

  • Author_Institution
    Coll. of fundamental Teaching, Sichuan Normal Univ., Chengdu, China
  • Volume
    1
  • fYear
    2009
  • fDate
    18-19 July 2009
  • Firstpage
    97
  • Lastpage
    100
  • Abstract
    The particle swarm optimization (PSO) first proposed by Eberhart and Kennedy, is a computational intelligence technique. The algorithm has shortcoming of premature convergence and slow convergence at the latter phase. In order to avoid these shortcomings we put forward the niche particle swarm optimization based on self-adaptive radius. This algorithm is proposed by the particle swarm optimization and Niche technology, it solves the PSOpsilas problem of premature convergence and slow convergence in latter phase and it improves the sharing mechanism at the role of algorithms through self-adaptive radius technology. Niche population is constituted by the particle which has the similar distance, then every particle is evolved by the PSO in each niche population, and the best individual is preserved in next generation. The algorithm is terminated until the satisfactory fitness value is found. The performance of NPSO is validated by Ackley function.
  • Keywords
    artificial intelligence; convergence; particle swarm optimisation; Ackley function; computational intelligence technique; fitness value; niche particle swarm optimization; niche population; niche technology; premature convergence; self-adaptive radius technology; slow convergence; Artificial intelligence; Artificial neural networks; Birds; Computational intelligence; Cultural differences; Education; Educational institutions; Information processing; Particle swarm optimization; Stochastic processes; Niche; PSO; Self-adaptive radius;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-0-7695-3699-6
  • Type

    conf

  • DOI
    10.1109/APCIP.2009.33
  • Filename
    5197005