An Adaptive Particle Swarm Optimization Algorithm Based on Cloud Model

摘要：

In this paper, an adaptive particle swarm optimization algorithm based on cloud model (C-APSO) is proposed. In the suggested method, the velocities of the all particles are adjusted based on the strategy that a particle whose fitness value is nearer to the optimal particle will fly with smaller velocity. Considering the properties of randomness and stable tendency of a normal cloud model, a Yconditional normal cloud generator is used to gain the inertial factors of the particles. The simulations of function optimization show that the proposed method has advantage of global convergence property and can effectively alleviate the problem of premature convergence.

关键词： particle swarm optimization adaptive particle swarm optimization cloud model

作者: Jinrong Zhu

作者单位: North China Electric Power University,Beijing 102206,China

会议类型: 国际会议

会议名称: 2010 International Conference on Material and Manufacturing Technology(2010材料与制造技术国际会议 ICMMT2010)

会议地点: 重庆

会议语种:英文

页码: 612-616

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）