摘要
利用模糊c均值(FCM)算法是一种最流行的模糊聚类的方法,因为它的效率,计算简单,容易实现.但是针对FCM对初始化敏感和易陷入局部最优解,在本文出了一种基于粒子群算法的模糊聚类.仿真实验结果表明了该方法对有效性和全局性优化.
Fuzzy c-means（FCM） algorithm is one of the most popular fuzzy clustering techniques because it is efficient,straightforward,and easy to implement.However,the FCM is sensitive to initialization and is easily trapped in local optima.In this paper,a hybrid fuzzy clustering method based on PSO is proposed.The simulation results show that the proposed method can optimize efficiently and globally.
出处
《佳木斯大学学报（自然科学版）》
CAS
2012年第2期281-284,共4页
Journal of Jiamusi University：Natural Science Edition
关键词
模糊C均值
模糊聚类
粒子群优化算法
Fuzzy c-means
fuzzy clustering
particle swarm optimization
