摘要
提出一种新的粗糙模糊C均值算法(RFCM),该算法基于粗糙集的上、下近似的概念改进了FCM的目标函数,从而改变了隶属度函数的分布,使得隶属度函数的分布更加合理,同时RFCM的时间复杂性比FCM更低。将RFCM用于图像的聚类,相对于FCM算法,图像的边缘更光滑,同时对初始隶属度矩阵敏感度更低。该算法具有较好的稳定性,是一种实用的算法。
Based on the rough set model proposed by Pawlak, a new fuzzy C-means algorithm-rough fuzzy C-means algorithm （RFCM） is presented. The algorithm employs a new objective function which incorporates the concepts of the upper approximation and the lower approximation in rough sets, and which produces better results than Fuzzy C-mean algorithm at time complexity, clustering precision, the sensitivity to initial degree of membership matrix. The better effect can be testified by many experiments.
出处
《国防科技大学学报》
EI
CAS
CSCD
北大核心
2007年第2期76-80,共5页
Journal of National University of Defense Technology
基金
国防科技大学资助项目(JC03-02-003)
