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.
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This book presents an extension of the aggregation operator of the generalized interval type-2 Sugeno integral using generalized type-2 fuzzy logic.
“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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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
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Produktdetaljer
ISBN
9783030164157
Publisert
2019-04-08
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet