遗传+模糊C-均值混合聚类算法

陈金山; 韦岗

遗传+模糊C-均值混合聚类算法

陈金山,
韦岗

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出版历程
- 收稿日期: 2000-04-06
- 修回日期: 2000-12-27
- 刊出日期: 2002-02-19

A hybrid clustering algorithm incorporating fuzzy C-means into canonical genetic algorithm

摘要

摘要: 本文提出了一种新的结合遗传算法(GA)和模糊C-均值算法(FCM)的混合聚类算法(HCA)。它通过对问题的解空间交替进行全局和局部搜索,达到快速收敛至全局最优解,较好地解决了GA在达到全局最优解前收敛慢和FCM算法容易陷入局部极小的问题。三组不同分布类型的数据聚类实验表明,该算法具有较好的通用性和有效性。
- 遗传算法; 模糊C-均值算法; 聚类
Abstract: A new Hybrid Clustering Algorithm (HCA) that incorporates the fuzzy C-means into the canonical genetic algorithm is proposed in this paper. The HCA speeds up convergence before the genetic algorithm reach the global optima, and eliminates fuzzy C-means trapped local minima by performing global search and local search alternatively. The experiments for clustering three data sets with different distributions show that the HCA has better generalization and effectiveness.

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