Dombi family of t-norms includes a parametric family of continuous strict t-norms, whose members are increasing functions of the parameter. This family of t-norms covers the whole spectrum of t-norms when the parameter is changed from zero to infinity. In this paper, we study a nonlinear optimization problem in which the constraints are defined as fuzzy relational equations (FRE) with the Dombi...

In this paper, we introduce the notion of an action $Y_X$as a generalization of the notion of a module,and the notion of a norm $vt: Y_Xto F$, where $F$ is a field and $vartriangle(xy)vartriangle(y') =$ $ vartriangle(y)vartriangle(xy')$ as well as the notion of fuzzy norm, where $vt: Y_Xto [0, 1]subseteq {bf R}$, with $bf R$  the set of all real numbers. A great many standard mappings on algebr...

Each t-norm can be identified with its Cayley tomonoid, which consists of pairwise commuting order-preserving functions from the real unit interval to itself. Cayley tomonoids provide an easily manageable, yet versatile tool for the construction of t-norms. To give evidence to this claim, we review and reformulate several construction methods that are known in the literature. We adopt, on the o...

In this paper we show a straight forward extension of the fuzzy Cohen’s-κ to Fleiss’-κ for the determination of classification agreements of fuzzy classifiers. In addition we investigate the influence of different interpretations of fuzzy intersection in terms of t-norms. These considerations are done for exemplary artificial data as well as for classification in image recognition for counting ...

We introduce nearly Frank t-norms as t-norms which are generated from Frank t-norms by means of a negation-preserving automorphism. We state basic properties of nearly Frank t-norms and we show their speci c role in the characterization of T -measures. 1 Basic facts about T -norms A t-norm (fuzzy conjunction) is a binary operation T : [0; 1]2 ! [0; 1] which is commutative, associative, nondecre...

We studied here the behavior of the t-norms at the point (1/2,1/2). We indicate why this point can be considered as significant in the specification of t-norms. Then, we suggest that the image of this point can be used to classify the t-norms. We consider some usual examples. We also study the case of parameterized tnorms. Finally using the results of this study, we propose a uniform method of ...

The combination of Fuzzy Logics and Description Logics (DLs) has been investigated for at least two decades because such fuzzy DLs can be used to formalize imprecise concepts. In particular, tableau algorithms for crisp Description Logics have been extended to reason also with their fuzzy counterparts. It has turned out, however, that in the presence of general concept inclusion axioms (GCIs) t...

This paper introduces and justifies a similaritybased concept of strict fuzzy orderings and provides constructions how fuzzy orderings can be transformed into strict fuzzy orderings and vice versa. We demonstrate that there is a meaningful correspondence between fuzzy orderings and strict fuzzy orderings. Unlike the classical case, however, we do not obtain a general one-to-one correspondence. ...

This paper deals with derivation of analytical structures of fuzzy PI controllers consisting of N ≥ 3 number of triangular input fuzzy sets and 2N − 1 number of trapezoidal output fuzzy sets on the universe of discourse of input and output variables, respectively, linear control rules, different T-norms, different T-conorms, different inference methods, and center of area defuzzification method...

The definition of t-norms and t-conorms of the class of Hamacher with multilayer feedforward artificial neural networks is achieved in this work. This fact lets to insert fuzzy knowledge into neural network before its training.