An efficient PSO-based clustering algorithm

Chun Wei Tsai, Ko Wei Huang, Chu Sing Yang, Ming Chao Chiang

研究成果: Conference contribution

摘要

Recently, particle swarm optimization (PSO) has become one of the most popular approaches to clustering problems because it can provide a higher quality result than deterministic local search method. The problem of PSO in solving clustering problems, however, is that it is much slower than deterministic local search method. This paper presents a novel method to speed up its performance for the partitional clustering problem-based on the idea of eliminating computations that are essentially redundant during its convergence process. In addition, the multistart strategy is used to improve the quality of the end result. To evaluate the performance of the proposed method, we compare it with several state-of-the-art methods in solving the data and image clustering problems. Our simulation results indicate that the proposed method can reduce from about 60% up to 90% of the computation time of the &-means and PSO-based algorithms to find similar or even better results.

原文English
主出版物標題KDIR 2010 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval
頁面150-155
頁數6
出版狀態Published - 2010 十二月 1
事件International Conference on Knowledge Discovery and Information Retrieval, KDIR 2010 - Valencia, Spain
持續時間: 2010 十月 252010 十月 28

出版系列

名字KDIR 2010 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval

Other

OtherInternational Conference on Knowledge Discovery and Information Retrieval, KDIR 2010
國家/地區Spain
城市Valencia
期間10-10-2510-10-28

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 資訊系統

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