Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6647
Title: Enhanced fuzzy clustering algorithm and cluster validity index for human perception
Authors: Başkır, M. Bahar
Türkşen, İsmail Burhan
Keywords: Fuzzy clustering
Cluster validity index
alpha-cut
Design alternative
Publisher: Pergamon-Elsevier Science Ltd
Abstract: In this study, we propose an enhanced fuzzy clustering algorithm related to a-cut interval descriptions of fuzzy numbers and a new cluster validity index, which occurs by a-cut intervals and adding two ad-hoc functions in the compactness and separability measures. As an application, we use the enhanced fuzzy clustering algorithm and its proposed validity index to rank supplier firms of a Turkish Machinery Corporation by design alternatives. In addition, the rankings of supplier firms are determined with a proposed decision measure. (C) 2012 Elsevier Ltd. All rights reserved.
URI: https://doi.org/10.1016/j.eswa.2012.05.049
https://hdl.handle.net/20.500.11851/6647
ISSN: 0957-4174
1873-6793
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

Show full item record



CORE Recommender

SCOPUSTM   
Citations

18
checked on Apr 13, 2024

WEB OF SCIENCETM
Citations

16
checked on Apr 13, 2024

Page view(s)

14
checked on Apr 15, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.