Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5913
Title: Recent advances in fuzzy system modeling
Authors: Türkşen, İsmail Burhan
Keywords: Computing with words
Fuzzy sets and logic
Meta-linguistic expressions
Type 1 and full type 2 fuzzy system models
Uncertainty
Issue Date: 2015
Publisher: Springer New York
Abstract: Decision making under uncertainty is an interdisciplinary research field.In this chapter, we attempt to create a framework for the human decision-making processes withType 1 and FullType 2 Fuzzy Logic methodology. For this purpose, we first present a brief review of the essentials of (1) Zadeh's rule basemodel,(2) Takagi and Sugeno's model which is partly a rule baseand partly a regression function, and (3) TÜrkşen's model of fuzzy regression functions where a fuzzy regressionfunction corresponds to each fuzzy rule in a fuzzy rule base model. Next, wereview the well-known fuzzy C-means (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 systemmodels.Forhispurpose, we provide an algorithm which lets one to generate Full Type 2 membership value distributions for a development of second-order fuzzy systemmodels 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 proposedalgorith.We present our applied results graphically for TD_Stockprice data with respect to two validity indices, namely (1) Çelikyılmaz-TÜrkşen and (2) Bezdek indices. © Springer Science+Business Media, LLC 2015.
URI: https://doi.org/10.1007/978-1-4614-3442-9_4
https://hdl.handle.net/20.500.11851/5913
ISBN: 9781461434429; 9781461434412
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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