Fuzzy Clustering Algorithm Based on Improved Particle Swarm Optimization and Its Application

摘要：

　　A fuzzy clustering algorithm based on improved particle swarm optimization was proposed in this paper.First reduce dimension of solution space,separate it into smaller solution space.In separated solution space,use of improved particle swarm optimization algorithm to search the sub-optimal solution as a chromosome of whole particle,use improved PSO to search global optimal solution.The particle solve the problem that swarm algorithm easy to fall into local optimal solution in high dimensional space,and the problem that the fuzzy clustering algorithm is sensitive to initial value problems.Simulation results show the effectiveness of this algorithm.

关键词： Particle swarm optimization Fuzzy C-Mean (FCM) Clustering

作者: Li Xue-yong Sun Jia-xia Fu Jun-hui Gao Guo-hong

作者单位: School of Information Engineer, Henan Institute of Science and Technology, Henan Xinxiang,453003, China

会议类型: 国际会议

会议名称: the 2010 International Conference on Frontiers of Manufacturing and Design Science(第一届制造与设计科学国际会议(ICFMD 2010))

会议地点: 重庆

会议语种:英文

页码: 4067-4071

在线出版日期: 2010-12-11（万方平台首次上网日期，不代表论文的发表时间）