Let I = ([0; 1];_;^; 0; 1), where _ and ^ are max and min, respectively. This algebra is the basic building block of fuzzy set theory and logic. Likewise, the algebra I = ([0; 1];_;^; 0; 1), where [0; 1] = f(a; b) : a; b 2 [0; 1], a bg, _, ^ are given coordinate-wise, and 0 and 1 are the bounds on [0; 1], is the relevant algebra for interval-valued fuzzy set theory and logic. A good share of th...

The paper considers an early approach toward a (fuzzy) set theory with a graded membership predicate and a graded equality relation which had been developed by the German mathematician D. Klaua in 1965. In the context of the mathematical fuzzy logic MTL of left-continuous t-norms we discuss some properties of these graded relations. We compare the simultaneous recursive definitions of these rel...

Aggregation processes are fundamental in any discipline where the fusion of information is of vital interest. For aggregating binary fuzzy relations such as equivalence relations or fuzzy orderings, the question arises which aggregation operators preserve specific properties of the underlying relations, e.g. T -transitivity. It will be shown that preservation of T -transitivity is closely relat...

In this paper we study generators of t-norms on the lattice LI of closed subintervals of the unit interval. Starting from a minimal set of axioms that any addition and multiplication operator on LI must fulfill, we investigate the properties of the additive and multiplicative generators on LI obtained using these arithmetic operators. We also investigate under which conditions the generators on...

Credit scoring analysis is an important activity, especially nowadays after a huge number of defaults has been one of the main causes of the financial crisis. Among the many different tools used to model credit risk, the recent development of rough set models has proved effective. The original development of rough set theory has been widely generalized and combined with other approaches to unce...

The notion of BCI-algebras was introduced by Iséki [3] which is a generalization of BCKalgebras [2]. This notion is originated from two different ways: one of the motivations is based on set theory, another motivation is from classical and nonclassical propositional calculi. Zadeh [8] introduced the notion of fuzzy sets. Many researchers have applied this concept to mathematical branches, such ...

The study of probabilistic models for random events, which are not simultaneously measurable or unsharp, requires new approaches to the modeling of uncertainty. The need for such an alternative theory comes back to the thirties of the twentieth century, since the classical (Kolmogorovian) probability theory could not explain events occurring in quantum physics. Nowadays, there are several scien...