In this paper the conventional fuzzy k-modes algorithm for clustering categorical data is extended by representing the clusters of categorical data with fuzzy centroids instead of the hard-type centroids used in the original algorithm. Use of fuzzy centroids makes it possible to fully exploit the power of fuzzy sets in representing the uncertainty in the classification of categorical data. To t...

We studied here on some simple examples the interaction between valuation family, parameters and ranking result. The ranking method studied is based upon the idea of associating with a fuzzy number a scalar value, its valuation, and using this valuation to compare and order fuzzy numbers. The valuation method considered was introduced initially by the Yager and Filev. This valuation consists in...

We propose three methods for obtaining solutions in fuzzy constraint networks and study their application to the problem of ordering fuzzy numbers. The techniques proposed may be classified as defuzzification functions which are applicable to any set of mutually dependent fuzzy numbers in which the dependence relationships are represented by means of metric constraints. We suggest the use of th...

The importance and difficulty of the problem of ranking fuzzy numbers is pointed out. Here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its valuation, and using this valuation to compare and order fuzzy numbers. Specifically we focus on expected value type valuations which are based upon the transformation of a fuz...

A fuzzy random variable is viewed as the imprecise observation of the outcomes in a random experiment. Since randomness and vagueness coexist in the same framework, it seems reasonable to integrate fuzzy random variables into imprecise probabilities theory. Nevertheless, fuzzy random variables are commonly presented in the literature as classical measurable functions associated to a classical p...

In this paper a linear Fuzzy Fredholm Integral Equation(FFIE) with arbitrary Fuzzy Function input and symmetric triangular (Fuzzy Interval) output is considered. For each variable, output is the nearest triangular fuzzy number (fuzzy interval) to the exact fuzzy solution of (FFIE).

Fuzzy variables are functions from credibility spaces to the set of real numbers. Based on the expected value of a fuzzy variable, the expected value of function of a simple fuzzy variable is studied. In order further to discuss the mathematical properties of fuzzy variables, some inequalities for fuzzy variables are derived based on the concepts of credibility measures and expected value opera...

The selection of features for classifying a pattern by means a fuzzy reasoning, is fundamental in order to obtain a reliable and significative response. The scope of this work is to compare three methods specialized for the extraction of features from images and, consequently, to study the ability of classification performed by applying a fuzzy inference system. The methods to be compared were:...

In the classical problems of mathematical programming the coefficients are assumed to be exactly known. This assumption is seldom satisfied by great majority of real-life problems. Starting from the idea of K.D. Jamison and W.A. Lodwick which solve a fuzzy linear programming problem (2001), a linear fractional programming problem with fuzzy coefficients is described and a solving algorithm is o...

* Department of Teacher Training in Electrical Engineering, Faculty of Technical Education, King’s Mongkut Institute of Technology North Bangkok. Abstract This paper describes fuzzy sliding-mode control (FSMC), a fuzzy logic control based upon variable structure techniques. A variable structure approach is designed with guaranteed stability properties. A ball and beam system is used here as an ...