The aim of this paper is to study induced (quasi-)uniformities in Kramosil and Michalek's fuzzy metric spaces. Firstly, $I$-uniformity in the sense of J. Guti'{e}rrez  Garc'{i}a and $I$-neighborhood system in the sense of H"{o}hle and u{S}ostak are induced by the given fuzzy metric. It is shown that the fuzzy metric and the induced $I$-uniformity will generate the same $I$-neighborhood system. ...

We deal with the constrained fuzzy arithmetic as introduced by G.J. Klir. Its implementation represents a problem because maxima of nonlinear functions have to be found. This increases the complexity of computations in comparison to the classical calculus of fuzzy quantities. We suggest a modi ed computational procedure which allows to calculate a suboptimal (i.e., inexact) solution with an acc...

The evaluation algorithm is based on the attributes of data objects. There is a certain correlation between attributes, and attributes are divided into key attributes and secondary attributes. The evaluation from the data objects in a hierarchical design based on key attributes can reduce the data size and algorithm complexity, and without prejudice on the basis of evaluation results can improv...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers ...

While desi ning radial basis function neural networks for classification, kzzy clustering is often used to position the hidden nodes in the input space. The main assumption of the clustering is that similar inputs produce similar out uts. In other words, it means that any two in ut patterns t o m the same cluster must be from the same cfass. Generalization is possible in the radial basis functi...

 This work develops a knowledge based system to autonomous navigation using Fuzzy Cognitive Maps (FCM). A new variant of FCM, named Event Driven-Fuzzy Cognitive Maps, (ED-FCM) is used to model decision tasks and/or make inference in the robot or mobile navigation. Fuzzy Cognitive Maps is a tool that modeling qualitative knowledge in minds maps structured way through concepts and causal relatio...

This paper deals problem of intelligent hybrid systems. Intelligent systems include neural networks (NN), fuzzy systems (FS) and genetic algorithms (GA). Each of these intelligent systems has certain properties (ability of learning, modelling, classifying, obtaining empirical rules, solving optimizing tasks ...) fitting specific kind of applications. Combination of these intelligent systems cre...

Fuzzy regression analysis using fuzzy linear models with symmetric triangular fuzzy number coefficient has been introduced by Tanaka et al. The goal of this regression is to find the coefficient of a proposed model for all given input-output data sets. In this paper, we propose a new 1716 E. Pasha et al method for computation of fuzzy regression. The method is constructed on the basis of minimi...

Let G be an intuitionistic fuzzy graph. Let u and v be two vertices of G. A subset D of V is called a fuzzy equitable dominating set if every v ∈ V − Dthere exist a vertex u ∈ D such that uv ∈ E(G) and |deg(u) − deg(v)| = 1 where deg(u) denotes the degree of vertex u and deg(v) denotes the degree of vertex v and μ2(vi, vj ) = μ1(vi) ∧ μ1(vj ), γ2(vi, vj ) = γ1(vi) ∨ γ1(vj ). The minimum cardina...