• DocumentCode
    2868378
  • Title

    An optimized quantum particle swarm algorithm based on the D-dimensional hyper-chaotic discrete system equation

  • Author

    Yangjun, Li ; Xia, Jin Yan ; Gao, Wang

  • Author_Institution
    Key Lab. of Instrum. Sci. & Dynamic Meas., North Univ. of China, Taiyuan, China
  • Volume
    13
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm inspired by social behavior patterns of organisms that research on such as fish schooling and bird flocking. This essay presents a new Quantum-behaved PSO (QPSO) algorithm using hyper-chaotic discrete system equation, as h-QPSO. The simulation results of the classical function have demonstrated that the h-QPSO algorithm is superior to the classical PSO algorithm and the quantum PSO algorithm in its performance.
  • Keywords
    discrete systems; particle swarm optimisation; D-dimensional hyper-chaotic discrete system equation; optimized quantum particle swarm algorithm; particle swarm optimization; population-based swarm intelligence algorithm; social behavior patterns; Algorithm design and analysis; Convergence; Equations; Mathematical model; Optimization; Particle swarm optimization; Presses; hyper-chaotic sequence; identical particle system; particle swarm optimization; search algorithm; seasonal fluctuation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5622858
  • Filename
    5622858