Extension of the Fuzzy Sugeno Integral Based on Generalized Type-2 Fuzzy Logic

Beschreibung

This book presents an extension of the aggregation operator of the generalized interval type-2 Sugeno integral using generalized type-2 fuzzy logic. This extension enables it to handle higher levels of uncertainty when adding any number of sources and types of information in a wide variety of decision-making applications. The authors also demonstrate that the extended aggregation operator offers better performance than other traditional or extended operators. The book is a valuables reference resource for students and researchers working on theory and applications of fuzzy logic in various areas of application where decision making is performed under high levels of uncertainty, such as pattern recognition, time series prediction, intelligent control and manufacturing.
Presents an extension of the aggregation operator of the generalized interval type-2 Sugeno integral using generalized type-2 fuzzy logic Demonstrates implementation in a modular neural network applied to face recognition and in an edge detector Offers a brief introduction to the potential use of the aggregation operators in real-world applications Discusses the basic concepts of type-1, interval type-2 and generalized type-2 fuzzy logic

Autor*in

Patricia Melin

Themen in »Extension of the Fuzzy Sugeno Integral Based on Generalized Type-2 Fuzzy Logic«

Sugeno Integral Fuzzy Measures Fuzzy Logic Generalized Interval Type-2 Fuzzy Logic Modular Neural Network Face Recognition Edge Detection

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“The exposure of the material is well structured and abundant detailed numeric examples are a visible asset of the publication. Overall, a useful reading material of interest to those involved in fuzzy aggregation models, their generalizations and applications.” (Witold Pedrycz, zbMath 1417.68003, 2019)

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