In this work, three topics which are important for the further development of fuzzy systems are chosen to be investigated. First, the mathematical aspects of fuzzy relational equations (FREs) are explored. Solving FREs is one of the most important problems in fuzzy systems. In order to identify the algebraic information of the fuzzy space, two new tools, called fuzzy multiplicative inversion an...

In this paper, the notions of $(T,S)$-composition matrix and$(T,S)$-interval-valued intuitionistic fuzzy equivalence matrix areintroduced where $(T,S)$ is a dual pair of triangular module. Theyare the generalization of composition matrix and interval-valuedintuitionistic fuzzy equivalence matrix. Furthermore, theirproperties and characterizations are presented. Then a new methodbased on $tilde{...

Recently, tuning the weights of the rules in Fuzzy Rule-Base Classification Systems is researched in order to improve the accuracy of classification. In this paper, a margin-based optimization model, inspired by Support Vector Machine classifiers, is proposed to compute these fuzzy rule weights. This approach not only  considers both accuracy and generalization criteria in a single objective fu...

in this paper, the synchronization of a new hyperchaotic complex system based on t-s fuzzy model is proposed. first the considered hyperchaotic system is represented by t-s fuzzy model equivalently. then by using the parallel distributed compensation (pdc) method and by applying linear system theory and exact linearization (el) technique, a fuzzy controller is designed to realize the synchroniz...

On the basis of the concept of the interval valued intuitionistic fuzzy sets introduced by K. Atanassov, the notion of interval valued intuitionistic fuzzy subsemimodule of a semimodule with respect to t-norm T and s-norm S is given and the characteristic properties are described. The homomorphic image and inverse image are investigated. In particular, by the help of the congruence relations on...

Keywords: Fuzzy relations BK subproduct Inference engine Interval-valued fuzzy sets Fuzzy sets and systems Membership functions a b s t r a c t The study of fuzzy relations forms an important fundamental of fuzzy reasoning. Among all, the research on compositional fuzzy relations by Bandler and Kohout, or the Bandler–Kohout (BK) subproduct gained remarkable success in developing inference engin...

In genetic fuzzy systems (GFS) the size of the problem has a huge influence in the performance of the obtained models, since i) the fuzzy rule bases learned suffer from exponential rule explosion when the number of variables increases, and ii) the convergence time increments with the number of examples. In this paper we present S-FRULER, a scalable distributed version of FRULER which is a GFS t...

⎯ In our paper, the properties of the simplest Takagi-Sugeno (T-S) fuzzy controller are first investigated. Next, based on the well-known Popov criterion with graphical interpretation, a sufficient condition in the frequency domain is proposed to guarantee the globally asymptotical stability of the simplest T-S fuzzy control system. Since this sufficient condition is presented in the frequency ...

Sophisticated fuzzy rule systems are supposed to be flexible, complete, consistent and compact (FC(3)). Flexibility, and consistency are essential for fuzzy systems to exhibit an excellent performance and to have a clear physical meaning, while compactness is crucial when the number of the input variables increases. However, the completeness and consistency conditions are often violated if a fu...

The analysis of data complexity is a proper framework to characterize the tackled classification problem and to identify domains of competence of classifiers. As a practical outcome of this framework, the proposed data complexity measures may facilitate the choice of a classifier for a given problem. The aim of this paper is to study the behaviour of a fuzzy rule based classification system and...