| 標題：Particle Swarm Optimization Algorithm and Its Application to Clustering Analysis |
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| 學年 | |
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| 學期 | |
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| 發表日期 | 2004/03/21 |
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| 作品名稱 | Particle Swarm Optimization Algorithm and Its Application to Clustering Analysis |
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| 作品名稱（其他語言） | |
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| 著者 | Chen, Ching-Yi; Ye, Fun |
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| 作品所屬單位 | 淡江大學電機工程學系 |
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| 出版者 | Piscataway: Institute of Electrical and Electronics Engineers (IEEE) |
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| 會議名稱 | Networking, Sensing and Control, 2004 IEEE International Conference on |
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| 會議地點 | 臺北市, 臺灣 |
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| 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. |
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| 關鍵字 | Clustering analysis;PSO |
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| 語言 | 英文 |
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| 收錄於 | |
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| 會議性質 | 國際 |
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| 校內研討會地點 | |
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| 研討會時間 | 20040321~20040323 |
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| 通訊作者 | |
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| 國別 | 中華民國 |
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| 公開徵稿 | Y |
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| 出版型式 | 紙本 |
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| 出處 | Networking, Sensing and Control, 2004 IEEE International Conference on, vol.2, pp.789-794 |
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| 相關連結 | |
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| SDGs | |
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