计算机技术与发展Issue(2)：78-81,85,5.DOI:10.3969/j.issn.1673-629X.2015.02.018
集粒度计算、蚁群算法与模糊思想的聚类算法
Clustering Algorithm Combined Granular Computing,Ant Colony Algorithm and Fuzzy Idea
摘要
Abstract
Fuzzy C-means clustering algorithm uses a random manner to select the cluster centers at the beginning,which makes fuzzy C-means clustering algorithm extremely sensitive to the selected initial cluster centers,and it is more easily to get the optimal solution in the local area,but the effect is not very well in the global scope. Ant colony clustering algorithm arbitrarily sets the probability of ants picking up or down the data object according to the priori knowledge,lack of rigorous mathematical basis. Focusing on the shortage of FCM algorithm and ant colony clustering algorithm,in this paper,apply the granular computing to the ant colony clustering algorithm,and combined the improved ant colony clustering algorithm and fuzzy C-means clustering algorithm,propose an improved fuzzy C-means clustering algorithm. Verified by experiments,the improved algorithm is better than the original algorithm on clustering effect.关键词
聚类/模糊C均值算法/粒度计算/蚁群算法Key words
clustering/fuzzy C-means algorithm/granular computing/ant colony algorithm分类
信息技术与安全科学引用本文复制引用
邵明来,秦亮曦..集粒度计算、蚁群算法与模糊思想的聚类算法[J].计算机技术与发展,2015,(2):78-81,85,5.基金项目
国家自然科学基金资助项目(61363027) （61363027）
