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

標題:K-Means Algorithm Based on Particle Swarm Optimization
學年
學期
發表日期2003/12/14
作品名稱K-Means Algorithm Based on Particle Swarm Optimization
作品名稱(其他語言)
著者Chen, Ching-Yi; Ye, Fun
作品所屬單位淡江大學電機工程學系
出版者
會議名稱2003 International Conference on Informatics, Cybernetics, and Systems
會議地點高雄, 臺灣
摘要Clustering analysis aims at discovering groups and identifying interesting distributions and patterns in data sets. It can help the user to distinguish the structure of data and simplify the complexity of data from mass information. A particle swarm optimization-based clustering technique that utilized the principles of K-means algorithm, called KPSO-clustering, is proposed in this article. We attempt to integrate the effectiveness of the K-means algorithm for partitioning data into a number of clusters, with the capability of PSO to bring it out of the local minima. Finally, the effectiveness of the KPSO-clustering is demonstrated on four artificial data sets.
關鍵字Clustering analysis;Particle swarm optimization;K-means
語言英文
收錄於
會議性質國際
校內研討會地點
研討會時間20031214~20031216
通訊作者
國別中華民國
公開徵稿Y
出版型式紙本
出處Proceedings of 2003 International Conference on Informations, Cybernetics, and Systems頁1470-1475
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