Hybridization of particle swarm optimization with the K-Means algorithm for clustering analysis
文献类型：会议论文
| 作者 | Shen H(申海); Zhu YL(朱云龙) ; Jin L(金莉); Zhu Z(朱珠)
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| 出版日期 | 2010 |
| 会议名称 | 2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010 |
| 会议日期 | September 23-26, 2010 |
| 会议地点 | Changsha, China |
| 关键词 | Cluster analysis Clustering algorithms Computation theory Convergence of numerical methods Function evaluation Pattern recognition Problem solving |
| 页码 | 531-535 |
| 中文摘要 | Clustering is an unsupervised classification technique which deals with pattern recognition problems. While traditional analytical methods suffer from slow convergence and the challenges of high-dimensional. Recent years, particle swarm optimization (PSO) has successfully been applied to a number of real world clustering problems with the fast convergence and the effectively for high-dimensional data. This paper presents a detailed overview of hybrid algorithms combining PSO with K-Means algorithm for solving clustering problem. For each algorithm, technical details that are required for applying clustering, such as its type, particle formulation, and the most efficient fitness functions are also discussed. Finally, a summary is given together with suggestions for future research. |
| 收录类别 | EI |
| 产权排序 | 1 |
| 会议主办者 | IEEE Beijing Section; Hunan University; Liverpool Hope University; Peking University; National Natural Science Foundation of China |
| 会议录 | Proceedings 2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010
 |
| 会议录出版者 | IEEE Computer Society |
| 会议录出版地 | Piscataway, NJ |
| 语种 | 英语 |
| ISBN号 | 978-1-4244-6438-8 |
| 源URL | [http://ir.sia.cn/handle/173321/8360]  |
| 专题 | 沈阳自动化研究所_工业信息学研究室 |
| 推荐引用方式 GB/T 7714 | Shen H,Zhu YL,Jin L,et al. Hybridization of particle swarm optimization with the K-Means algorithm for clustering analysis[C]. 见:2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010. Changsha, China. September 23-26, 2010. |
入库方式： OAI收割
来源：沈阳自动化研究所
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