In this work, we show that single input single output (SISO) fuzzy inference systems based on Fuzzy Relational Inference (FRI) with implicative interpretation of the rule base are universal approximators under suitable choice of operations for the other components of the fuzzy system. The presented proofs make no assumption on the form or representations of the considered fuzzy implications and...

s 107 ultimate moment); and productivity Ip = (/mat + /man + It)/Iman. Practically, for the fuzzification process (/mat, Ir,a,, It, and Ia are interpreted as fuzzy goals and Isi and Ip as fuzzy constraints), an exponential membership function lk = e -klxl (where k is the importance coefficient) is proposed. Thus by this procedure, the optimal investment is alternative a3, and the hierarchizatio...

s 107 ultimate moment); and productivity Ip = (/mat + /man + It)/Iman. Practically, for the fuzzification process (/mat, Ir,a,, It, and Ia are interpreted as fuzzy goals and Isi and Ip as fuzzy constraints), an exponential membership function lk = e -klxl (where k is the importance coefficient) is proposed. Thus by this procedure, the optimal investment is alternative a3, and the hierarchizatio...

I n this paper, we review a new definition of fuzzy functional dependency based on conditional probability and i ts application to approximate data reduction related to operation of projection in classical relational database in order to construct fuzzy integrity constraints [l]. W e introduce the concept of partial fuzzy functional dependency which expresses the fact that a given attribute X d...

In classical Boolean logic, data is represented as being either entirely true or entirely false. In most real world phenomena however, it is rare that en entity will be absolutely true or absolutely false. When designing a system, Boolean logic lacks the tools necessary to deal with this kind of uncertainty. Using fuzzy logic we were able to develop a system that is able to deal with uncertaint...

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...