Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6777
Title: Genetic type-2 fuzzy classifier functions
Authors: Çelikyılmaz, Aslı
Türkşen, İsmail Burhan
Keywords: type-2 fuzzy functions
classification
genetic algorithms
Issue Date: 2008
Publisher: IEEE
Source: Annual Meeting of the North-American-Fuzzy-Information-Processing-Society -- MAY 19-22, 2008 -- New York, NY
Abstract: A new type-2 fuzzy classifier function system is proposed for uncertainty modeling using genetic algorithms GT2FCF. Proposed method implements a three-phase learning strategy to capture the uncertainties in fuzzy classifier function systems induced by learning parameters, as well as fuzzy classifier functions. Hidden structures are captured with the implementation of improved fuzzy clustering. The optimum uncertainty interval of the type-2 fuzzy membership values are captured with a genetic learning algorithm. The results of the experiments show that the GT2FCF is comparable - if not superior- to well-known benchmark methods in terms of area under the receiver operating curve (AUC) performance measure.
URI: https://hdl.handle.net/20.500.11851/6777
ISBN: 978-1-4244-2351-4
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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