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
Issue Date: 2013
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

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