计算机应用与软件2016，Vol.33Issue(12)：234-237,274,5.DOI:10.3969/j.issn.1000-386x.2016.12.056
优化的人工鱼群和FCM的混合聚类算法
AN IMPROVED CLUSTERING ALGORITHM BASED ON OPTIMIZED ARTIFICIAL FISH SWARM ALGORITHM AND FCM
摘要
Abstract
An improved clustering algorithm which combines optimized artificial fish swarm algorithm with fuzzy C-means algorithm is proposed because the fuzzy C-means clustering algorithm is easy to fall into local extreme value and it is sensitive to the initial clustering centers.This algorithm optimizes the behavior of artificial fish and introduces the communication behavior in order to improve the search precision and efficiency by adjusting the parameters of artificial fish in a self-adapted way using the fitness function of fuzzy C-means. Compared with other algorithms,simulation results show that the improved algorithm has a better effect on both the convergence speed and search accuracy.关键词
人工鱼群算法/模糊/C-均值/通信行为/适应度函数/自适应Key words
Artificial fish swarm algorithm/Fuzzy C-means/Communication behavior/Fitness function/Adaptive分类
信息技术与安全科学引用本文复制引用
戴月明,赵莉莉..优化的人工鱼群和FCM的混合聚类算法[J].计算机应用与软件,2016,33(12):234-237,274,5.基金项目
国家高技术研究发展计划项目（2013AA 040405）。 （）
