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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 |
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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