重庆理工大学学报：自然科学2012，Vol.26Issue(8)：71-78,8.
一种改进的和声搜索模糊聚类算法
Research of Fuzzy Clustering Algorithm Based on Modified Harmony Search
摘要
Abstract
As fuzzy clustering algorithm is more sensitive to initial values and cluster centers, the paper presents a modified harmony to rapidly and efficiently find the optimal cluster centers, which adjusts pitch rate and random bandwidth of original harmony search algorithm to accelerate convergence rate. The weighted dimension is used to select feature in order to improve the clustering performance and the clustering quality evaluation function is defined to improve the clustering quality. Finally, the paper uses standard dataset to validate some algorithms and the results show that the proposed clustering algorithm outperforms other similar algorithms.关键词
和声搜索/维度加权/特征选择/聚类Key words
harmony search/weighted dimension/feature selection/clustering分类
计算机与自动化引用本文复制引用
王华秋,罗江..一种改进的和声搜索模糊聚类算法[J].重庆理工大学学报：自然科学,2012,26(8):71-78,8.基金项目
教育部基金资助项目 （）
重庆市教委科学研究项目 （）
