An inductive approach for learning fuzzy relational rules is described. Fuzzy relational rules are rules in which fuzzy relations in the antecedent parts of the rules are allowed. These rules allow us to use an extended model of rule with a greather capability to represent knowledge in a similar human way, but with an additional complexity in the search process.

I. The need for comparative evaluation of performance of different systems of fuzzy connectives in soft computing applications This paper continues our work on developing new methods and tools for comparative assessment of the adequacy of diierent many-valued implication operators and other fuzzy connectives. To deal with the problem of selecting the optimal fuzzy logic connectives, new methods...

This paper presents an attempt to embed and unify research on intuitionistic fuzzy (IF) relations into a broad, formal yet intuitive framework inspired by fuzzy relational calculus. The need for the resulting “IF relational calculus” is motivated in semantical terms of vagueness and uncertainty; its basic definitions and results are introduced, and opportunities and challenges specific to intui...

in previous studies we first concentrated on utilizing crisp simulationto produce discrete event fuzzy systems simulations. then we extendedthis research to the simulation of continuous fuzzy systems models. in this paperwe continue our study of continuous fuzzy systems using crisp continuoussimulation. consider a crisp continuous system whose evolution depends ondifferential equations. such a ...

Fuzzy set theory has been extensively applied to extend various database models(conceptual and logical) and resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. So this paper reviews fuzzy logical database models, in which fuzzy relational databases are discussed.

Fuzzy set theory has been extensively applied to extend various database models and resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. To satisfy the need of modeling complex objects with imprecision and uncertainty, recently many researches have been concentrated on fuzzy object-oriented database models. This paper reviews fuz...

Usable implementations of fuzzy relational database systems are very rare considering the long time of research on the subject. The existing solutions are usually either obsolete or related to a specific application. The research group that authors belong to aims at producing a general system capable of using priority fuzzy logic with databases. The system consists of a fuzzy extension of a rel...

We propose herein a novel unified framework that uses a developed hybrid fuzzy-neuro system in order to evaluate the impact of inheritance aspects on the evolvability of a class library, and to study the relevance of using inheritance as indicator of class interface stability with respect to version change. To this goal, we propose a novel computational granular unified framework that is cognit...

Relational clustering is an extension of clustering for relational data. Fuzzy c-Medoids (FCMdd) based linear fuzzy clustering extracts intrinsic local linear substructures from relational data. However this linear clustering was affected by noise or outliers because of using Euclidean distance. Alternative Fuzzy c-Means (AFCM) is an extension of Fuzzy c-means, in which a modified distance meas...

 Minimum and maximum operators are two well-known t-norm and s-norm used frequently in fuzzy systems. In this paper, two different types of fuzzy inequalities are simultaneously studied where the convex combination of minimum and maximum operators is applied as the fuzzy relational composition. Some basic properties and theoretical aspects of the problem are derived and four necessary and suffi...