互联网 qkzz.net
全刊杂志网:首页 > 女性 > 文章正文
刊社推荐

改进的粒子群优化模糊C均值聚类算法


  摘 要:针对传统模糊C均值聚类算法(FCM)存在对初值敏感和易陷入局部收敛的缺陷,利用改进的粒子群算法对FCM进行优化,提出一种新的模糊C均值聚类算法Improved PSOFCM,并建立基于熵的聚类有效性函数,对聚类算法的性能进行客观评价。数据集实验表明,Improved PSOFCM算法不仅能克服传统FCM算法的不足,而且在聚类正确率和有效性上也优于基于粒子群与基于遗传优化的FCM算法。

  关键词:模糊C均值聚类;粒子群优化;熵;聚类有效性

  中图分类号:O159;TP18文献标志码:A

  文章编号:1001-3695(2010)07-2520-03

  doi:10.3969/j.issn.1001-3695.2010.07.033

  Fuzzy C-means clustering algorithm based on improved PSO

  WEN Zhong-wei, LI Rong-jun

  (College of Business Administration, South China University of Technology, Guangzhou 510640, China)

  Abstract:Traditional FCM clustering algorithm includes the problems of local optimal and sensitivity to initial values. The improved PSO algorithm was used to optimize FCM.This paper proposed a new fuzzy C-means clustering algorithm Improved PSOFCM and constituted a clustering efficiency function based on Shannon entropy to evaluate the performance of clustering algorithm in the impersonal way. Numerical examples illustrate that the Improved PSOFCM can overcome the deficiency of FCM, and have better clustering accuracy and efficiency than FCM based on PSO and GA.

  Key words:fuzzy C-means(FCM) clustering; particle swarm optimization(PSO); entropy; clustering efficiency

......
很抱歉,暂无全文,若需要阅读全文或喜欢本刊物请联系《计算机应用研究》杂志社购买。
欢迎作者提供全文,请点击编辑
分享:
 

了解更多资讯,请关注“木兰百花园”
分享:
 
精彩图文


关键字
支持中国杂志产业发展,请购买、订阅纸质杂志,欢迎杂志社提供过刊、样刊及电子版。
关于我们 | 网站声明 | 刊社管理 | 网站地图 | 联系方式 | 中图分类法 | RSS 2.0订阅 | IP查询
全刊杂志赏析网 2017