%0 Journal Article
%T An Improvement Clustering Algorithms Based on Max-t1 Norm<br>MAX—t1范数聚类算法的改进
%A YAN De-Qin CHI Zhong-Xian
%A <br>闫德勤
%A 迟忠先
%J 计算机科学
%D 2004
%I 
%X A comparative study between transitive closure fuzzy clustering algorithm and the fuzzy clustering algorithm based on t_1-norm with fuzzy matrix are presented. The study shows that for describing the fuzzy relation of two elements max-t_1 fuzzy transitive relation is more critical than that of max-min fuzzy transitive relation. That is the reason why t_1-norm dose not has max-t transitivity. Besides, in this paper a new algorithm to determine equivalent classes is given. With the new algorithm the fuzzy clustering algorithm based on t_1-norm with fuzzy matrix is more reasonable. Experiments show the effectiveness of the new algorithm.
%K Fuzzy clustering
%K Max-t_1 norm
%K Clustering algorithm
%K Fuzzy matrix<br>MAX-t1范数
%K 聚类算法
%K 模糊聚类
%K 模糊矩阵
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=E7AF1A27D5DC3BBD&yid=D0E58B75BFD8E51C&vid=4AD960B5AD2D111A&iid=B31275AF3241DB2D&sid=6425DAE0271BB751&eid=E114CF9BB47B65BE&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=5