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《山东大学学报(理学版)》 ›› 2025, Vol. 60 ›› Issue (1): 74-82.doi: 10.6040/j.issn.1671-9352.4.2023.0215

• • 上一篇    

基于新型阴影集的模糊C均值聚类算法

国栋凯1,张钦然1,李小南2,易黄建1*   

  1. 1.西北大学信息科学与技术学院, 陕西 西安 710127;2.西安电子科技大学数学与统计学院, 陕西 西安 710126
  • 发布日期:2025-01-10
  • 通讯作者: 易黄建(1985— ),女,副教授,博士,研究方向为光学图像三维重建、三支决策模型与应用、智能信息处理.E-mail: yhj2014@nwu.edu.cn
  • 作者简介:国栋凯(1996— ),男,硕士研究生,研究方向为三支决策、阴影集、模糊聚类分析等. E-mail: 1159044933@qq.com*通信作者:易黄建(1985— ),女,副教授,博士,研究方向为光学图像三维重建、三支决策模型与应用、智能信息处理.E-mail: yhj2014@nwu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(61906154);陕西省教育厅青年创新团队资助项目(21JP123)

Fuzzy C-means clustering algorithm based on new shadowed sets

GUO Dongkai1, ZHANG Qinran1, LI Xiaonan2, YI Huangjian1*   

  1. 1. School of Information Science and Technology, Northwest University, Xian 710127, Shaanxi, China;
    2. School of Mathematics and Statistics, Xidian University, Xian 710126, Shaanxi, China
  • Published:2025-01-10

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摘要： 提出一种基于五区域阴影集的模糊C均值(fuzzy C-means, FCM)算法,利用FCM算法得到对象簇的隶属度,引入五区域阴影集,将对象划分为核心区域、次核心区域、阴影区域、次边缘区域和边缘区域,分析次核心区域得到阈值ω,通过核心区域和次核心区域中隶属度μ≥ω的对象簇得到聚类结果,在8个公开数据集中进行实验。本文提出的算法相比于其余3种算法在7个数据集上取得了最佳的聚类结果。

关键词: 三支决策, 模糊聚类, 三支聚类, 五区域阴影集

Abstract: A fuzzy C-means(fuzzy C-means, FCM)clustering algorithm based on five-region shadowed sets is proposed in this paper. The membership degree of the object to the cluster is obtained by the FCM algorithm. The object is divided into core region, semi-core region, shadow region, semi-negative region and negative region according to the membership degree by introducing the five-region shadowed sets. Then, a threshold value ω is obtained by analyzing the semi-core region. The objects whose membership degree μ≥ω in the core region and semi-core region are classified into this cluster to get the final clustering result. Experiments are carried out on 8 public data sets with other 3 clustering algorithms, compared with the other 3 algorithms, the algorithm proposed in this paper achieves the best clustering results on 7 data sets. The experimental results show that the proposed algorithm in this paper is superior to 3 other algorithms.

Key words: three-way decision, fuzzy clustering, three-way clustering, five-region shadowed sets

中图分类号: 

  • TP301.6
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