计算机技术与发展2015，Vol.25Issue(12)：28-31,4.DOI:10.3969/j.issn.1673-629X.2015.12.007
一种改进的K-means蚁群聚类算法
An Improved K-means Ant Colony Clustering Algorithm
摘要
Abstract
Existed K-means ant colony clustering algorithm carries out K -means algorithm operation,fast and roughly determines the clustering center,then according to rough clustering center,ant colony clustering algorithm is conducted again to solve the problem of low convergence speed effectively. The research shows that the existed K-means any colony clustering algorithm doesn't improve the defect of converging to non-global optimal in late iteration. In order to solve this problem,a modified K-means ant colony clustering algorithm is presented. At the end of each iteration,randomly select one or more clusters,and then choose the point from the selected cluster with minimum pheromones for mutation,the mutation selecting node to another cluster,evaluation value is calculated to judge whether to mu-tate. Experimental results show that the average and worst results indicated by F value are better than the original algorithm,effectively solving the problem that is easy to converge to non-global optimal and premature,but it takes a longer running time.关键词
聚类/K-means算法/蚁群聚类算法/聚类组合/变异Key words
clustering/K-means algorithm/ant colony clustering algorithm/clustering combination/variation分类
信息技术与安全科学引用本文复制引用
李振,贾瑞玉..一种改进的K-means蚁群聚类算法[J].计算机技术与发展,2015,25(12):28-31,4.基金项目
国家自然科学基金资助项目(61202227) （61202227）
