计算机应用与软件Issue(2)：275-278,4.DOI:10.3969/j.issn.1000-386x.2014.02.074
基于混沌和动态变异蛙跳的模糊聚类算法
FUZZY CLUSTERING ALGORITHM BASED ON CHAOTIC AND DYNAMIC MUTATION SHUFFLED FROG LEAPING ALGORITHM
摘要
Abstract
Fuzzy C-means(FCM)clustering algorithm is prone to fall into the solution of local minimum and is sensitive to initial value. Aiming at these drawbacks,we present a fuzzy C-means clustering algorithm which is based on chaotic and dynamic mutation shuffled frog leaping algorithm (SFLA ).In this algorithm,frog population is initialised with Tent chaotic sequence to enhance the diversity of the population and to improve the quality of initial solution,and the corresponding mutation probability is selected according to the fitness variance of each frog.Then the improved shuffled frog leaping algorithm is employed to optimise the FCM algorithm,and to get the global optimum finally.Simulation results on artificial data and classic dataset show that compared with the SMSFLA-FCM,SFLA-FCM and FCM clustering algorithms,the new algorithm (CMSFLA-FCM)has stronger optimisation ability and better clustering effect.关键词
模糊C-均值算法/蛙跳算法/混沌和动态变异Key words
Fuzzy C-means clustering/Shuffled frog leaping algorithm/Chaotic and dynamic mutation分类
信息技术与安全科学引用本文复制引用
刘悦婷..基于混沌和动态变异蛙跳的模糊聚类算法[J].计算机应用与软件,2014,(2):275-278,4.基金项目
甘肃省自然科学基金项目（1112RJZA028）；甘肃联合大学科研能力提升计划一般项目 （）
