An Improved Particle Swarm Optimization Algorithm

摘要：

According to the particle swarm optimization algorithm (PSO) exist precocious and local convergence problem, Put forward a kind of improved particle swarm optimization algorithm, the gradient descent method (BP algorithm) as a particle swarm operator embedded in particle swarm algorithm, By static function approximation to test of the improvement of the particle swarm optimization algorithm, results show that the improved algorithm not only increased global optimization ability, but also avoid the immature convergence problem.

关键词： particle swarm optimization premature Neural Networks

作者: Weidong Ji Keqi Wang

作者单位: College of Mechnical and Electrical Engineering Northeast Forestry University Harbin, China College of Computer Science and Technology Harbin Normal University Harbin, China

会议类型: 国际会议

会议名称: 2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 585-589

在线出版日期: 2011-12-24（万方平台首次上网日期，不代表论文的发表时间）