JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2025, Vol. 60 ›› Issue (1): 74-82.doi: 10.6040/j.issn.1671-9352.4.2023.0215

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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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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

CLC Number: 

  • TP301.6
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