%0 Journal Article
%T Hybrid clustering algorithm based on artificial bee colony and K-means algorithm<br>一种结合人工蜂群和K-均值的混合聚类算法
%A BI Xiao-jun
%A GONG Ru-jiang
%A <br>毕晓君
%A 宫汝江
%J 计算机应用研究
%D 2012
%I 
%X The traditional K-means clustering algorithm is too dependent on the initial clustering centers. With regards to this, this paper proposed a mixed clustering method based on the improvement artificial colony algorithm and the K-means algorithm. The new method combined the advantages of regulating ability of global optimization and local optimization with rapid convergence of K-means clustering algorithm to improve the robustness of the algorithm. Experiments show that the clustering result of the new method is significantly improved, not only the stability.
%K artificial bee colony
%K clustering algorithm
%K K-means<br>人工蜂群
%K 聚类算法
%K K-均值
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=AB480754FB5F26FE16D1C6D478CD6489&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=B31275AF3241DB2D&sid=2D8A2D26AFF207D2&eid=5A6F5D4235F292B9&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10