A Fast Fuzzy C-means Clustering Algorithm Based on Soft and Hard Clustering

摘要：

The paper puts forward a kind of fast fuzzy C-means clustering algorithm based on soft and hard clustering. The fast fuzzy C-means clustering algorithm inserts one layer of hard c-means clustering algorithm in front of FCM and regards the cluster centers of hard c-means clustering algorithm as the initial values of fuzzy cluster centers.It is very meaningful for a large number of data clustering.Experimental results show that the method has a shorter adjusting iteration course and a faster convergence speed than FCM

关键词： Fuzzy c-means clustering algorithm (FCM) Soft clustering Hard clustering

作者: Ji NaiHua Yao Huiping Wang Yingjie

作者单位: Computer Engineering Institute,Qingdao Technological University,Qingdao Shandong School of Science,Qingdao Technological University,Qingdao Shandong Information Science and Engineering Institute,Dalian University,Dalian Liaoning

会议类型: 国际会议

会议名称: 2009 International Conference on Information,Electronic and Computer Science(2009 国际信息、电子与计算机工程学术会议)

会议地点: 青岛

会议语种:英文

页码: 638-641

在线出版日期: 2009-11-21（万方平台首次上网日期，不代表论文的发表时间）