An Optimized Quantum Particle Swarm Algorithm Based On the D-dimensional Hyper-chaotic Discrete System Equation

摘要：

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.

关键词： identical particle system hyper-chaotic sequence search algorithm particle swarm optimization seasonal fluctuation

作者: Li Yangjun Jin Yanxia WangGao

作者单位: Key Laboratory of Instrumentation Science&Dynamic Measurement (North University of China) Ministry of Education Shanxi, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 471-474

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）