People interested in the practical applications of fuzzy systems theory are the intended audience for this book. Just enough of the theory of fuzzy systems is presented to enable the reader to follow the applications described in subsequent chapters. The reader needs no prior knowledge of fuzzy systems theory.

The book consists of 16 chapters and an index. Chapter1 points out the role of fuzzy systems theory as a formalism for handling uncertainty. This chapter also briefly compares fuzzy systems theory with probability theory and surveys the current and possible future applications of fuzzy systems theory. Chapter 2 deals with the basics of fuzzy systems theory: fuzzy sets, fuzzy numbers, and fuzzy propositions. Chapter3 treats fuzzy relations and their use in fuzzy reasoning via the operation of composition of fuzzy relations. Each of chapters 4 through 16 deals with a particular application of fuzzy systems theory: regression models, statistical decision making, quantification theory, mathematical programming, evaluation, diagnosis, control, human reliability models, intelligent robots, image recognition, databases, information retrieval, and expert systems. Each chapter ends with a list of references.

The book contains no exercises. It is an English translation of a Japanese original; some errors, such as the use of the work “paragraph” for “chapter” on page 39, may be due to this translation. Other errors (they are few) are typographical, such as the failure to use the notation for fuzzy numbers consistently on page 34.

The book uses examples liberally to illustrate ideas. The large number of applications considered makes it a valuable reference for practitioners who wish to employ fuzzy systems theory in their work.