Please use this identifier to cite or link to this item:
Title: Improved fuzzy clustering
Authors: Çelikyılmaz, Aslı
Türkşen, İsmail Burhan
Issue Date: 2009
Abstract: The new fuzzy system modeling approach based on fuzzy functions implements fuzzy clustering algorithm during structure identification of the given system. This chapter introduces foundations of fuzzy clustering algorithms and compares different types of well-known fuzzy clustering approaches. Then, a new improved fuzzy clustering approach is presented to be used for fuzzy functions approaches to re-shape membership values into powerful predictors. Lastly, two new cluster validity indices are introduced to be used to validate the improved fuzzy clustering algorithm results. © 2009 Springer-Verlag Berlin Heidelberg.
ISBN: 9783540899235
ISSN: 1434-9922
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Show full item record

CORE Recommender


checked on Sep 23, 2022

Page view(s)

checked on Feb 6, 2023

Google ScholarTM



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