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计算机工程 ›› 2006, Vol. 32 ›› Issue (20): 18-21. doi: 10.3969/j.issn.1000-3428.2006.20.007

• 博士论文 • 上一篇    下一篇

基于粒子群算法的量子谐振子模型

冯 斌,须文波   

  1. (江南大学信息工程学院,无锡214122)

  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2006-10-20 发布日期:2006-10-20

Quantum Oscillator Model of Particle Swarm System

FENG Bin, XU Wenbo   

  1. (School of Information Engineering, Southern Yangtze University, Wuxi 214122)
  • Received:1900-01-01 Revised:1900-01-01 Online:2006-10-20 Published:2006-10-20

摘要: 对目前人工智能界研究热点粒子群算法进行了探讨,将量子谐振子势能场引入了粒子群系统,建立了基于粒子群算法的量子谐振子模型,有效地提高了运算速度。通过测试函数的仿真实验证明了量子谐振子粒子群算法的全局收敛能力优于一般粒子群算法。

关键词: 粒子群优化算法, 量子谐振子模型, 参数控制, 优化

Abstract: Particle swarm optimization is an evolutionary search technique motivated by the behavior of social organisms. Quantum oscillator model of PSO algorithm is established and a method of parameter control is provided in this paper, and a new swarm intelligence algorithm (QOPSO)is designed. The vast number of experiment results show that the new swarm intelligence algorithm has much stronger global searching ability compared to the classical PSO algorithm.

Key words: Particle swarm optimization (PSO), Quantum oscillator model, Parameter control, Optimization

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