Abstract Numerous research papers and several engineering applications have proved that the fuzzy set theory is an intelligent effective tool to represent complex uncertain information. In multi-criteria decision-making (fuzzy MCDM) methods, information system control-theoretic models, qualitative are extracted from expert’s knowledge as linguistic variables modeled by linear/non-linear numbers...

In this paper, the researchers proposed a new method to rank fuzzy numbers by median value of fuzzy numbers. The median value can be used as a crisp approximation with respect to a fuzzy quantity. Therefore, a method for ordering the fuzzy numbers is defined accordingly. This method can effectively rank various fuzzy numbers, their images and overcome the shortcomings of the previous techniques.

The paper presents the operation of two neuro-fuzzy systems of an adaptive type, intended for solving problems of the approximation of multi-variable functions in the domain of real numbers. Neuro-fuzzy systems being a combination of the methodology of artificial neural networks and fuzzy sets operate on the basis of a set of fuzzy rules “if-then”, generated by means of the self-organization of...

This paper investigates the approximation behaviour of the KH interpolative fuzzy controllers. First, in accordance with the remarks in [20], it is pointed out that it is a fuzzy generalization of the Shepard operator. Shepard operator has thoroughly studied by approximation theorist since the mid 70s. Exploiting the aforementioned relationship, we establish analog results on the approximation ...

This paper presents a new extension of fuzzy sets: R-fuzzy sets. The membership of an element of a R-fuzzy set is represented as a rough set. This new extension facilitates the representation of an uncertain fuzzy membership with a rough approximation. Based on our definition of R-fuzzy sets and their operations, the relationships between R-fuzzy sets and other fuzzy sets are discussed and some...