A Novel Fuzzy Clustering Based on Particle Swarm Optimization

摘要：

In order to overcome the shortcomings of Fuzzy C-means Algorithm such as the local optima and sensitivity to initialization, a new PSO-based fuzzy algorithm is discussed in this paper. The new algorithm uses the capacity of global search in PSO algorithm, and solves the problems of FCM. The experiment shows that the algorithm avoids the local optima and increases the convergence speed.

关键词： Cluster analysis Particle swarm optimization Fuzzy C-means algorithm Global optimization

作者: Lili Li Xiyu Liu Mingming Xu

作者单位: School of Information Science and Engineering, Shandong Normal University, Jinan Shandong 250014 School of Management, Shandong Normal University, Jinan Shandong 250014 Ping An of China Co. Ltd. Jinan branch 250001

会议类型: 国际会议

会议名称: 第一届国际教育信息技术及应用研讨会(2007 1st International Symposium on Information Technologies and Applications in Education(ISITAE 2007))

会议地点: 昆明

会议语种:英文

在线出版日期: 2007-11-23（万方平台首次上网日期，不代表论文的发表时间）