Titlebook: An Introduction to Computing with Fuzzy Sets; Analysis, Design, an Witold Pedrycz Book 2021 The Editor(s) (if applicable) and The Author(s)

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Peter Buxmann,Heiner Diefenbach,Thomas Hesstworks are highlighted and mechanisms enhancing the interpretability of the network. The gradient-based learning is discussed as a generic mechanism of supervised learning. Selected architectures of neurofuzzy systems involving autoencoders and relational factorization are put forward.

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Fuzzy Neurocomputing,tworks are highlighted and mechanisms enhancing the interpretability of the network. The gradient-based learning is discussed as a generic mechanism of supervised learning. Selected architectures of neurofuzzy systems involving autoencoders and relational factorization are put forward.

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1868-4394 ed facets of fuzzy sets, it will appeal to a broad readership in both academe and industry. It is also ideally suited as a textbook for graduate and undergraduate students in science, engineering, and operations research..978-3-030-52802-7978-3-030-52800-3Series ISSN 1868-4394 Series E-ISSN 1868-4408

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Higher Type, Higher Order Fuzzy Sets and Hybrid Fuzzy Sets,of single elements. Hybridization, on the other hand, is about bringing several formalisms of information granules and using them in an orthogonal setting. This situation is visible in fuzzy probabilities.

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Die Integration von Softwaresystemenlong time almost since the very inception of fuzzy sets. In contrast to interval analysis and set theory where the estimation of bounds of the interval constructs has not attracted a great deal of attention and seemed to be somewhat taken for granted, an estimation of membership degrees (and members