Particle swarm optimization algorithm and its application to clustering analysis
學年 92
學期 1
發表日期 2004-01-01
作品名稱 Particle swarm optimization algorithm and its application to clustering analysis
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 N.Y.: IEEE (Institute of Electrical and Electronic Engineers)
會議名稱 2004 IEEE International Conference on Networking, Sensing and Control
會議地點 Taiwan
摘要 Clustering analysis is applied generally to pattern recognition, color quantization and image classification. It can help the user to distinguish the structure of data and simplify the complexity of data from mass information. The user can understand the implied information behind extracting these data. In real case, the distribution of information can be any size and shape. A particle swarm optimization algorithm-based technique, called PSO-clustering, is proposed in this article. We adopt the particle swarm optimization to search the cluster center in the arbitrary data set automatically. PSO can search the best solution from the probability option of the social-only model and cognition-only model. This method is quite simple and valid, and it can avoid the minimum local value. Finally, the effectiveness of the PSO-clustering is demonstrated on four artificial data sets.
關鍵字
語言 en
收錄於
會議性質 國內
校內研討會地點
研討會時間
通訊作者
國別
公開徵稿 Y
出版型式
出處 2004 IEEE International Conference on Networking, Sensing and Control, 2, pp.789-794
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