In this paper, we present a general framework for the study of interval type-2 rough fuzzy sets by using both constructive and axiomatic approaches. First, several concepts and properties of interval type-2 fuzzy sets are introduced. Then, a pair of lower and upper interval type-2 rough fuzzy approximation operators with respect to a crisp binary relation is proposed. Classical representations ...

Planning resources for a supply chain is a major factor determining its success or failure. In this paper we introduce an Interval Type-2 Fuzzy Logic model of a distribution network. It is believed that the additional degree of uncertainty provided by Interval Type-2 Fuzzy Logic will allow for better representation of the uncertainty and vagueness present in resource planning models. First, the...

Type-2 fuzzy sets are growing in popularity as, for certain applications they model uncertainty and imprecision better than type1 fuzzy sets. However, type-2 fuzzy sets can be difficult to understand and explain. Recent work has introduced embedded type-2 fuzzy sets and the Representation Theorem which enable us to discuss type-2 fuzzy sets in a different way. In particular they allow for alter...

This paper presents the development and design of a graphical user interface and a command line programming toolbox for construction, edition and observation of Interval Type-2 Fuzzy Inference Systems. The Interval Type-2 Fuzzy Logic System Toolbox (IT2FLS), is an environment for interval type-2 fuzzy logic inference system development. Tools that cover the different phases of the fuzzy system ...

This paper presents the theory and design of interval type-2 fuzzy logic systems (FLSs) because of computational complexity of using general type-2 fuzzy set (T2FS) in type-2 fuzzy system. We propose an efficient and simplified method to compute the input and antecedent operations for interval type-2 FLSs; one that is based on a general inference formula for them. We introduce the concept of up...

In this paper we give a complete description of an interval type-2 fuzzy logic system based on geometry. We compare our novel defuzzification technique with type-reduction.

This paper presents some theoretical considerations about the variance of a fuzzy set and introduces covering–based algorithm for computing bounds an interval Type–2 set. The proposed obtains all possible variances unlike other algorithms which are based on center centroid to obtain relative is proven be always bigger than absolute variance. A comparison given through different examples where s...