基于遗传算法的图论聚类方法

针对传统图论聚类算法对初始聚类中心的敏感性以及聚类结果与样本输入次序等问题,提出了基于遗传算法进行图论聚类分析的基本原理和实现方法.实验结果表明,遗传算法应用于图论聚类分析能够搜索到更为精确的聚类中心值,其结果明显好于传统图论聚类算法.

Graph-Theoretical Clustering Method Based on Genetic Algorithms

To solve the problem of sensitivity with the original clustering center and clustering results depended on the order of the input example in common graph-theoretical clustering algorithm,the basic rules and procedures of applying genetic algorithms to graph theoretical clustering analysis are studied.Computing results show that applying it to clustering can accurately locate the clustering centers and is superior to common graph-theoretical clustering algorithm.