教師資料查詢 | 類別: 期刊論文 | 教師: 余 繁 YU FUN (瀏覽個人網頁)

標題:Alternative KPSO-Clustering Algorithm
學年93
學期2
出版(發表)日期2005/06/01
作品名稱Alternative KPSO-Clustering Algorithm
作品名稱(其他語言)
著者余繁; Ye, Fun; Chen, Ching-yi
單位淡江大學電機工程學系
出版者淡江大學
著錄名稱、卷期、頁數淡江理工學刊=Tamkang journal of science and engineering 8(2), pp.165-174
摘要This paper presents an evolutionary particle swarm optimization (PSO) learning-based method to optimally cluster N data points into K clusters. The hybrid PSO and K-means algorithm with a novel alternative metric, called Alternative KPSO-clustering (AKPSO), is developed to automatically detect the cluster centers of geometrical structure data sets. The alternative metric is known has more robust ability than the common-used Euclidean norm. In AKPSO algorithm, the special alternative metric is considered to improve the traditional K-means clustering algorithm to deal with various structure data sets. For testing the performance of the proposed method, this paper will show the experience results by using several artificial and real data sets. Simulation results compared with some well-known clustering methods demonstrate the robustness and efficiency of the novel AKPSO method.
關鍵字Clustering;Particle Swarm Optimization;K-means
語言英文(美國)
ISSN1560-6686
期刊性質國內
收錄於
產學合作
通訊作者
審稿制度
國別中華民國
公開徵稿
出版型式,紙本
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