An Improved Fuzzy Clustering Algorithm

摘要：

Fuzzy C-means clustering algorithm(FCM) is sensitive to its initialization of value and noise data and easy to fall into local minimum points,while it cant get the global optimal solution.On the basis that particle swarm optimization algorithm(PSO) is of the whole optimization and quite good local optimization with higher speed to converge to the optimization,this paper proposed an improved fuzzy clustering algorithm(IFCM).The experimental results show that the algorithm has better global optimal solution,overcomes the shortcomings of traditional fuzzy C-means clustering algorithm.Clustering results are obviously better than single use of PSO algorithm and FCM algorithm.

关键词： data clustering particle swarm optimization algorithm fuzzy clustering fuzzy C-means clustering algorithm

作者: Tianwu Zhang Gongbing Guo

作者单位: Computer Science & Engineering Department Henan Institute of Engineering Xinzheng,China College of Computer & Communication Engineering Zhengzhou University of light Industry Zhengzhou,Chi

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 508-511

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）