Fuzzy-Rough Intrigued Harmonic Discrepancy Clustering-Reference-Cited by-同舟云学术

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Fuzzy-Rough Intrigued Harmonic Discrepancy Clustering

Published:2023-10 Issue:10 Volume:31 Page:3305-3318
ISSN:1063-6706
Container-title:IEEE Transactions on Fuzzy Systems
language:
Short-container-title:IEEE Trans. Fuzzy Syst.

Author:

Yue Guanli¹^ORCID,Qu Yanpeng²^ORCID,Yang Longzhi³^ORCID,Shang Changjing⁴^ORCID,Deng Ansheng¹,Chao Fei⁵^ORCID,Shen Qiang⁴^ORCID

Affiliation:

1. Information Technology College, Dalian Maritime University, Dalian, China

2. College of Artificial Intelligence, Dalian Maritime University, Dalian, China

3. Department of Computer and Information Sciences, Northumbria University, London, U.K.

4. Department of Computer Science, Faculty of Business and Physical Sciences, Aberystwyth University, Aberystwyth, U.K.

5. Department of Computer Science, Xiamen University, Xiamen, China

Funder

Industry-University-Research Innovation Fund for Chinese Universities

Dalian High-Level Talent Innovation Program

Sêr Cymru II COFUND Fellowship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/91/10272989/10050169.pdf?arnumber=10050169

Reference47 articles.

1. Fuzzy C-Means clustering algorithm for data with unequal cluster sizes and contaminated with noise and outliers: Review and development

2. Interval type-2 enhanced possibilistic fuzzy c-means clustering for gene expression data analysis;sotudian,2021

3. Intuitionistic fuzzy c-means clustering algorithm based on a novel weighted proximity measure and genetic algorithm

4. An Implementation of the Mean Shift Algorithm

5. Robust spatial intuitionistic fuzzy C-means with city-block distance clustering for image segmentation

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1. FRCM: A fuzzy rough c-means clustering method;Fuzzy Sets and Systems;2024-03

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