Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7095
Title: Multi-central general type-2 fuzzy clustering approach for pattern recognitions
Authors: Golsefid, S. Malek Mohamadi
Zarandi, Mohammad Hossein Fazel
Türkşen, İsmail Burhan
Keywords: General type-2 fuzzy clustering
General type-2 fuzzy membership
Cluster center uncertainty
Multi-central cluster
Validity index
Verification index
Issue Date: 2016
Publisher: Elsevier Science Inc
Abstract: This paper presents a new approach to general type-2 fuzzy clustering called Multi-central general type-2 fuzzy clustering model. This model mainly focuses on uncertainty associated with the cluster centers. In this model, a set of points is considered as the center for each cluster. The membership values to the clusters are defined as general type-2 fuzzy sets including primary and secondary variables. Primary variable indicates the degree of belonging to the central objects, and the secondary variables indicate the degree of belonging of the central objects to the center of the cluster. There is not any type reduction or defuzzification for updating cluster prototypes in the proposed clustering algorithm. The compatible indexes with the proposed model are defined for validation and verification of the clustering process and results. Several experimental results are given to evaluate the performance of the proposed Multi-central general type-2 fuzzy clustering. The results also compared with the results of the type-1 fuzzy clustering model. (C) 2015 Published by Elsevier Inc.
URI: https://doi.org/10.1016/j.ins.2015.08.027
https://hdl.handle.net/20.500.11851/7095
ISSN: 0020-0255
1872-6291
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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