%0 Journal Article
%T K-Harmonic Means Clustering with Simulated Annealing<br>基于模拟退火的K调和均值聚类算法
%A LIU Guo-Li
%A ZHEN Xiao-Min
%A <br>刘国丽
%A 甄晓敏
%J 计算机系统应用
%D 2011
%I 
%X K-means algorithm is a frequently-used methods of partition clustering.However,it greatly depends on the initial values and converges to local minimum.In K-harmonic means clustering,harmonic means fuction which apply distance from the data point to all clustering centers is used to solves the problem that clustering result is sensitive to the initial valve instead of the minimum distance.Although the problem above is solved,the problem converged to local minimum is still existed.In order to obtain a glonal ...
%K clustering
%K K-means
%K K-Harmonic means
%K simulated annealing
%K local minimum<br>聚类
%K K均值
%K 调和均值
%K 模拟退火
%K 局部最小
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=E78B2DC5A1D4B0FCB4C9F7B525B29FDD&yid=9377ED8094509821&vid=A04140E723CB732E&iid=DF92D298D3FF1E6E&sid=869807E2D7BED9EC&eid=39EEF47180459690&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=4