Medoids-based fuzzy relational clustering generates clusters of objects based on relational data, which records pairwise similarity or dissimilarities among objects. Compared with single-medoid based approaches, multiple-weighted medoids has shown superior performance in clustering. In this paper, we present a new version of fuzzy relational clustering in this family called fuzzy clustering wit...

Estimation of distribution algorithm for optimization of neural networks for intrusion detection system p. 9 Neural network implementation in reprogrammable FPGA devices-an example for MLP p. 19 A new approach for finding an optimal solution and regularization by learning dynamic momentum p. 29 Domain dynamics in optimization tasks p. 37 Nonlinear function learning by the normalized radial basi...

Bipolar max-? equations, with ? a triangular norm, have recently become popular research topic embedded in the broad field of fuzzy relational equations. In this paper, we lift work from restrictive setting real unit interval — obfuscating underlying lattice-theoretical essence to general complete distributive symmetric residuated lattices, allowing build upon vast body knowledge on unipolar su...

A fuzzy restriction may be visualized as an elastic constraint on the values that may be assigned to a variable. In terms of such restrictions, the meaning of a proposition of the form "x is P," where x is the name of an object and P is a fuzzy set, may be expressed as a relational assignment equation of the form R(A(x)) = P, where A(x) is an implied attribute of x, R is a fuzzy restriction on ...

Fuzzy relational identi"cation builds a relational model describing a system's behaviour by a nonlinear mapping between its variables. In this paper, we propose a new fuzzy relational algorithm based on the simpli"ed max}min relational equation. The algorithm presents an adaptation method applied to the gravity-centre of each fuzzy set based on the error integral value between the measured and ...

The paper dealswith systems of fuzzy relation equations known in the literature as eigen fuzzy set equations, aswell aswith systems of related fuzzy relation inequalities.Ourmain results are algorithms for computing the greatest and the smallest solutions to the considered systems of fuzzy relation inequalities, and algorithms for computing the greatest solutions to the considered systems of fu...

Fuzzy relational identification builds a relational model describing system’s behaviour by a nonlinear mapping between its variables. In this paper, we propose a new fuzzy relational algorithm based on simplified max-min relational equation. The algorithm presents an adaptation method applied to gravity-center of each fuzzy set based on error integral value between measured and predicted system...

The aim of this thesis is to extend the fuzzy relational product calculations from binary to ternary relations, and apply the ternary fuzzy relational product calculations to processing of the URBS data. It is demonstrated that, by ternary fuzzy relational product calculations, the respondents with the similar cognitive structures can be clustered into groups and cognitive structures of those g...