Type-2 Fuzzy Logic: Theory and Applications, Oscar Castillo; Patricia Melin
Автор: Reghis Название: Classical and Fuzzy Concepts in Mathematical Logic and Applications, Professional Version ISBN: 0849331978 ISBN-13(EAN): 9780849331978 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents coverage of the fundamentals of two-valued logic, multivalued logic, and fuzzy logic. Exploring the parallels between classical and fuzzy mathematical logic, this book examines the use of logic in computer science, addresses questions in automatic deduction, and describes efficient computer implementation of proof techniques.
Автор: J. Harris Название: Fuzzy Logic Applications in Engineering Science ISBN: 9048170346 ISBN-13(EAN): 9789048170340 Издательство: Springer Рейтинг: Цена: 130590.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Fuzzy logic is a relatively new concept in science applications. Hitherto, fuzzy logic has been a conceptual process applied in the field of risk management. Its potential applicability is much wider than that, however, and its particular suitability for expanding our understanding of processes and information in science and engineering in our post-modern world is only just beginning to be appreciated.
Written as a companion text to the author's earlier volume "An Introduction to Fuzzy Logic Applications", the book is aimed at professional engineers and students and those with an interest in exploring the potential of fuzzy logic as an information processing kit with a wide variety of practical applications in the field of engineering science and develops themes and topics introduced in the author's earlier text.
Автор: Xiaodong Liu; Witold Pedrycz Название: Axiomatic Fuzzy Set Theory and Its Applications ISBN: 3642101461 ISBN-13(EAN): 9783642101465 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume examines Axiomatic Fuzzy Sets (AFS), in which fuzzy sets and probability are treated in a unified and coherent fashion. It presents AFS as a rigorous mathematical theory as well as a flexible methodology for the development of intelligent systems.
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