%0 Journal Article %T A Novel Dynamic Clustering Algorithm Based on Tabu Search
基于Tabu搜索的聚类算法研究 %A ZHONG Jiang %A WU Zhong-Fu %A WU Kai-Gui %A YANG Qinag Computer College of Chongqing University %A Chongqing %A
钟将 %A 吴中福 %A 吴开贵 %A 杨强 %J 计算机科学 %D 2005 %I %X Cluster analysis aims at answering two main questions: how many clusters there are in the data set and where they are located. Usually, the traditional clustering algorithms only focus on the last problem. In order to solve the two problems at the same time, this paper proposes a novel dynamic clustering algorithm called DCBIT, which is based on the immune network and Tabu search. The algorithm includes two phases, it begins by running im- mune network algorithm to find a candidate clustering center set, and then it employs Tabu search to search the opti- mum number of clusters and the location of each cluster according to the candidate centers. Experimental results show that the hew algorithm has satisfied convergent probability and convergent speed. %K Dynamic clustering %K Artifical immune network %K Tabu search
Tabu搜索 %K 聚类算法 %K 聚类分析 %K DCBIT %K 人工免疫网络算法 %K 收敛概率 %U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=8ED5567330F19610&yid=2DD7160C83D0ACED&vid=9971A5E270697F23&iid=CA4FD0336C81A37A&sid=9D453329DCCABB94&eid=0584DB487B4581F4&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=8