计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (13): 157-160.

• 数据库、信号与信息处理 • 上一篇    下一篇

新型区间数据模糊C-均值聚类算法

岳明道   

  1. 宿州学院 机械与电子工程学院,安徽 宿州 234000
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-05-01 发布日期:2011-05-01

Novel fuzzy C-means clustering algorithm for interval data

YUE Mingdao   

  1. Mechanical and Electric Engineering College,Suzhou University,Suzhou,Anhui 234000,China

  • Received:1900-01-01 Revised:1900-01-01 Online:2011-05-01 Published:2011-05-01

摘要: 在传统模糊C-均值聚类算法的基础上,提出了一种新型区间值数据模糊聚类算法。运用区间分割策略改进了区间距离的计算公式,成功解决了区间距离计算方法存在的缺陷。提出了区间值数据模糊聚类的数学模型,并拓广模糊C-均值算法对区间值数据进行聚类。仿真验证了所提出算法的有效性。

关键词: 聚类分析, 区间值数据, 区间距离, 模糊C-均值

Abstract: Based on the traditional fuzzy C-means clustering algorithm,a new fuzzy C-means clustering algorithm for interval data clustering is proposed. Firstly,one interval dividing strategy is adopted to improve the method of calculating interval distance.Secondly,a fuzzy clustering math model for the interval data is proposed;then,the fuzzy C-means clustering algorithm is extended to cluster the interval data.Finally,the effectiveness of the algorithm is demonstrated by some experiments.

Key words: clustering analysis, interval data, interval data distance, fuzzy C-means clustering