蚁群聚类组合算法的研究

Algorithm based on combination of ACA and clustering analysis

聚类分析作为数据挖掘中一个重要的组成部分,主要用于在潜在的数据中发现有价值的数据分布和数据模式。在研究基本蚁群聚类模型、信息熵以及LF算法和K-means算法的基础上,提出了一种蚁群聚类组合算法策略。

As one of the most important domains of data mining, clustering analysis is mainly used for identifying valuable data distribution and data mode in the potential data. Based on the study of basic clustering model, information entropy and two classical clustering analysis algorithms （LF and K- means）, this paper puts forward an algorithm which is based on the combination of ACA and clustering analysis.