Robust hesitant fuzzy partitional clustering algorithms and their applications in decision making-Reference-Cited by-同舟云学术

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Robust hesitant fuzzy partitional clustering algorithms and their applications in decision making

Published:2023-09 Issue: Volume:145 Page:110212
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Chao Kun,Zhao Hua,Xu Zeshui,Cui Feng

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Software

Reference33 articles.

1. Data clustering: 50 years beyond K-means;Jain;Pattern Recognit. Lett.,2010

2. Some methods for classification and analysis of multivariate observations;Macqueen,1967

3. Sur la division des corps matériels en parties (French);Steinhaus;Bull. Acad. Polon. Sci. C1.III.,1956

4. Least squares quantization in PCM;Lloyd;IEEE Trans. Inform. Theory.,1982

5. ISODATA, a Novel Method of Data Analysis and Pattern Classification;Ball,1965

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Consistency and consensus checking and improving methods for group decision-making with hesitant fuzzy preference relations;Journal of the Operational Research Society;2024-04-05

2. Improved interval type-2 fuzzy K-means clustering based on adaptive iterative center with new defuzzification method;International Journal of Approximate Reasoning;2023-09

3. More on complex hesitant fuzzy graphs;AIMS Mathematics;2023

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