A Particle Swarm Optimization Algorithm With Momentum Factor

摘要：

The basic particle swarm optimization algorithm updated particles velocity only by the current particles velocity, the personal best position and the excellent particle position. Considering the influence of the previous changes among the current particles velocity, in this paper, the updating formula of particles velocity was mended by appending momentum factor, an improved particle swarm optimization algorithm with momentum factor was proposed. The simulation results show that the improved algorithm has higher accuracy and quicker convergence velocity than the basic particle swarm optimization algorithm.

关键词： Particle Swarm Optimization (PSO) Momentum factor Convergence velocity

作者: Jinxia Ren Shuai Yang

作者单位: School of Mechanical and Electronic Engineering Jiangxi University of Science and Technology Ganzhou, China

会议类型: 国际会议

会议名称: 2011 Fourth International Symposium on Computational Interlligence and Design 第四届计算智能与设计国际会议 ISCID 2011

会议地点: 杭州

会议语种:英文

页码: 19-21

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）