%0 Journal Article
%T Improved Density Weighted Fuzzy C Means Algorithm<br>一种改进的密度加权的模糊C聚类算法
%A WANG Xing-Fu
%A CHENG Yong-Yuan
%A QIN Qi-Xian
%A <br>王行甫
%A 程用远
%A 覃启贤
%J 计算机系统应用
%D 2012
%I 
%X Fuzzy C Means algoritba,a is popular soft clustering algorithm. It has been applied in many engineering fields. Density weighted FCM is its variant, which can solve FCM＇s problem： sensitive to outlier and noise data. However, performances of both algorithms are heavily depend on proper initial cluster centers. This paper proposes a novice algorithm： Improved density weighted FCM based on nearest neighbor pair and its density, simulation results show initial center produced by the algorithm are very close to final cluster center. Thus IDWFCM can convergent very quickly and imorove the Performance_
%K fuzzy C means
%K improved density weighted fuzzy C means
%K initial cluster center
%K nearest neighbor data pair
%K density<br>模糊聚类
%K 基于密度加权的模糊C聚类
%K 初始聚类中心
%K 最近邻居节点对
%K 密度
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=57C6AD9B0ADA0537CEF8ACFB056C5E0E&yid=99E9153A83D4CB11&vid=659D3B06EBF534A7&iid=9CF7A0430CBB2DFD&sid=1D67BE204FBF4800&eid=E089FDF3CDAE8561&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=7