%0 Journal Article
%T An Integrated Fuzzy Clustering Algorithm GFC for Switching Regressions<br>关于切换回归的集成模糊聚类算法 GFC
%A WANG Shi-tong
%A JIANG Hai-feng
%A LU Hong-jun
%A <br>王士同
%A 江海峰
%A 陆宏钧
%J 软件学报
%D 2002
%I 
%X In order to solve switching regression problems, many approaches have been investigated. In this paper, anintegrated fuzzy clustering algorithm GFC that combines gravity-based clustering algorithm GC with fuzzy clustering is presented. GC, as a new hard clustering algorithm presented here, is based on the well-known Newton's Gravity Law. The theoretic analysis shows that GFC can conve rge to a local minimum of the object function. Experimental results show that GFC for switching regression problems has better performance than standard fuzzy clustering algorithms, especially in terms of convergence speed.
%K switching regression
%K fuzzy clustering
%K gravity-based clustering<br>切换回归
%K 模糊聚类
%K 引力聚类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=853F90A3549BEE27&yid=C3ACC247184A22C1&vid=FC0714F8D2EB605D&iid=F3090AE9B60B7ED1&sid=356A00866E8A0E8E&eid=3F70AF647A5D3F8D&journal_id=1000-9825&journal_name=软件学报&referenced_num=0&reference_num=15