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Title: Type 1 and Full Type 2 Fuzzy System Models
Authors: Türkşen, İsmail Burhan
Keywords: [No Keywords]
Issue Date: 2015
Publisher: Springer-Verlag Berlin
Series/Report no.: Studies in Fuzziness and Soft Computing
Abstract: We first present a brief review of the essentials fuzzy system models: Namely (1) Zadeh's rulebase model, (2) Takagi and Sugeno's model which is partly a rule base and partly a regression function and (3) Turksen fuzzy regression functions where a fuzzy regression function correspond to each fuzzy rule. Next we review the well known FCM algorithm which lets one to extract Type 1 membership values from a given data set for the development of Type 1 fuzzy system models as a foundation for the development of Full Type 2 fuzzy system models. For this purpose, we provide an algorithm which lets one to generate Full Type 2 membership value distributions for a development of second order fuzzy system models with our proposed second order data analysis. If required one can generate Full Type 3, ..., Full Type n fuzzy system models with an iterative execution of our algorithm. We present our application results graphically for TD_Stockprice data with respect to two validity indeces, namely: (1) elikyilmaz-Trksen and (2) Bezdek indeces.
ISBN: 978-3-319-19683-1; 978-3-319-19682-4
ISSN: 1434-9922
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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