Fuzzy Logic Theory And Applications

No previous knowledge of fuzzy set theory and fuzzy logic is required for understanding the material covered in the book. Although knowledge of basic ideas of classical (nonfuzzy) set theory and classical (two-valued) logic is useful, fundamentals of these subject areas are briefly overviewed in the book. In addition, basic ideas of neural networks, genetic algorithms, and rough sets are also explained. This makes the book virtually self-contained.

This book describes new methods for building intelligent systems using type-2 fuzzy logic and soft computing (SC) techniques. The authors extend the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers. This book is intended to be a major reference tool and can be used as a textbook.

An introductory book that provides theoretical, practical,and application coverage of the emerging field of type-2 fuzzylogic control Until recently, little was known about type-2 fuzzy controllersdue to the lack of basic calculation methods available for type-2fuzzy sets and logic—and many different aspects of type-2fuzzy control still needed to be investigated in order to advancethis new and powerful technology. This self-contained referencecovers everything readers need to know about the growing field. Written with an educational focus in mind, Introduction toType-2 Fuzzy Logic Control: Theory and Applications uses acoherent structure and uniform mathematical notations to linkchapters that are closely related, reflecting the book’scentral themes: analysis and design of type-2 fuzzy controlsystems. The book includes worked examples, experiment andsimulation results, and comprehensive reference materials. The bookalso offers downloadable computer programs from an associatedwebsite. Presented by world-class leaders in type-2 fuzzy logic control,Introduction to Type-2 Fuzzy Logic Control: Is useful for any technical person interested in learningtype-2 fuzzy control theory and its applications Offers experiment and simulation results via downloadablecomputer programs Features type-2 fuzzy logic background chapters to make thebook self-contained Provides an extensive literature survey on both fuzzy logic andrelated type-2 fuzzy control Introduction to Type-2 Fuzzy Logic Control is aneasy-to-read reference book suitable for engineers, researchers,and graduate students who want to gain deep insight into type-2fuzzy logic control.

Fuzzy Set Theory: Foundations and Applications serves as a simple introduction to basic elements of fuzzy set theory. The emphasis is on a conceptual rather than a theoretical presentation of the material. Fuzzy Set Theory also contains an overview of the corresponding elements of classical set theory - including basic ideas of classical relations - as well as an overview of classical logic. Because the inclusion of background material in these classical foundations provides a self-contained course of study, students from many different academic backgrounds will have access to this important new theory.

Nowadays, voluminous textbooks and monographs in fuzzy logic are devoted only to separate or some combination of separate facets of fuzzy logic. There is a lack of a single book that presents a comprehensive and self-contained theory of fuzzy logic and its applications. Written by world renowned authors, Lofti Zadeh, also known as the Father of Fuzzy Logic, and Rafik Aliev, who are pioneers in fuzzy logic and fuzzy sets, this unique compendium includes all the principal facets of fuzzy logic such as logical, fuzzy-set-theoretic, epistemic and relational. Theoretical problems are prominently illustrated and illuminated by numerous carefully worked-out and thought-through examples. This invaluable volume will be a useful reference guide for academics, practitioners, graduates and undergraduates in fuzzy logic and its applications.

The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, “The only satisfactory description of uncertainty is probability.