基于免疫遗传算法的模糊C均值聚类算法应用研究  

Applicationof Fuzzy C-means Clustering Algorithm Based on Immune Genetic Algorithm

作　　者：李鹏松[1] 石卓[1] 刘欣[1] Li Pengsong;Shi Zhuo;Liu Xin(Science College,Northeast Electric Power University,Jilin Jilin 132012)

机构地区：[1]东北电力大学理学院,吉林吉林132012

出　　处：《东北电力大学学报》2018年第3期79-83,共5页Journal of Northeast Electric Power University

摘　　要：应用硬聚类算法及模糊聚类算法解决数据分类问题时,在迭代过程中容易陷入局部极小.本文提出了一种基于免疫遗传算法的模糊C均值聚类算法,克服了现有算法的缺点.将本文算法应用于葡萄酒和鸢尾花数据集,得出结果说明其有效性.When the hard clustering algorithm and fuzzy clustering algorithm are used to solve the problem of data classification,it is easy to fall into the local minimum in the iterative process. In this paper,a fuzzy Cmeans clustering algorithm based on immune genetic algorithm is proposed,which overcomes the shortcomings of the existing algorithms.This algorithm is applied to the dataset of wine and iris,and the results show its effectiveness.

关 键 词：模糊C均值 免疫遗传算法 葡萄酒 鸢尾花 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]