In this paper we deal with mathematical programming problems with fuzzy constraints. Fuzzy solutions are obtained by means of a parametric approach in conjuntion with evolutionary techniques. Some important characteristics of the evolutionary algorithm are a natural representation of solutions , a problem-independent technique for constraint satisfaction, tournament selection, complete generati...

In this work we consider a very general principle for fuzzy rule interpolation methods based on an interpretation of the generalized modus ponens rule in terms of closeness relations. Then we present two particular instances of the general principle when the closeness relations are defined from parametric families of similarity fuzzy relations on the input and output spaces. The case of multipl...

One parametric classify (Maximum likelihood classify, MLC for short) and two non-parametric classifiers (Adaptive resonance theory mappings and this study. Base on the confusion matrix and the pixels fuzzy analysis, the nonparametric classifier may be a more preferable approach than the parametric classifier for some remote sensing applications and deserves further investigation. The ARTMAP cla...

This paper develops an adaptive fuzzy control of nonlinear system class. In this method, we investigated the possibilities offered by the fuzzy systems of TakagiSugeno type in terms of approximation capacity of the continuous nonlinear functions and we exploited the Lyapunov theory to establish a parametric adaptation law, ensuring the total stability of the system. Finally, simulation results ...

The fuzzy representation of the edges has been widely studied in different works. Generally, for each pixel, the authors use membership degrees linearly proportional to the magnitude of the gradient at that position of the image. This would be equivalent to using a triangular membership functions on the gradient magnitude. In this work we study the use of parametric functions in the transformat...

The present paper describes the development of a modular neuro-fuzzy system, designated for enhanced and flexible fault diagnosis. Some specific neural algorithms for identification, recognition, evaluation and classification of the process parametric values are created and applied in the systems structure. The so-developed neuro-fuzzy system is then applied for fault diagnosis in an industrial...

The problem of decision making under imprecise environments are widely spread in real life decision situations. We present a method of object recognition from imprecise multi observer data, which extends the work of Roy and Maji [J. Compu. Appl. Math. 203(2007) 412-418] to generalized intuitionistic fuzzy soft set theory. The method involves the construction of a comparison table from a general...

Abstract: An adaptive identifier for neuro-fuzzy control system nonlinear dynamic object operating in conditions of uncertainty intrinsic properties and the environment. The algorithms of structural and parametric identification in real time are a combination of an identification algorithm coefficients of linear management and methods of the theory of interactive adaptation. Adaptive neuro-fuzz...