… Chapter 1 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 …

… used successfully in a variety of applications [1], [10], [25], [28], [31], [33]. In neural fuzzy
systems [1], [10], vectors of fuzzy sets are used both to train a fuzzy neural network and as inputs …

… theory and applications are just what the readers desired. But if we think about it, the situation
of research on fuzzy systems … publication of Fuzzy Systems Theory and Its Applications, for …

… The book has proved to be of great utility to anyone interested in fuzzy set theory and its
applications. For us, it has consistently been one of the most frequently used books. However, …

… application examples are shown. Chapters 3 and 4 present the basic theoretical framework
of crisp and fuzzy set theory… linear systems and the fuzzy relation of a nonlinear fuzzy system. …

… rule extraction method, we discuss how to optimize the composite neural network and
describe its application to blood cell classification. Then we show examples of composite …

… , applications of fuzzy set theory to existing methodology or to real problems. In addition, the
transition from fuzzy set theory to fuzzy … improve the design of fuzzy systems and make them …

… of the current fuzzy systems and fuzzy control research is appealing: the fuzzy control system
technology is moving toward a solid foundation as part of the modern control theory. The …

… A list of basic texts in fuzzy sets and their applications is provided in … it is better to state it
clearly in the face of newcomers to the theory, as it sheds light on potential limitations of the fuzzy …

… fuzzy' a fuzzy set is. We will show in the following that a proper fuzziness of a fuzzy set is
important for the performance of a fuzzy system… the interpretability of a fuzzy system. For example…