The mathematical framework for studying of a fuzzy approximate reasoning is presented in this paper. Two important defuzzification methods (Area defuzzification and Height defuzzification) besides the center of gravity method which is the best well known defuzzification method are described. The continuity of the defuzzification methods and its application to a fuzzy feedback control are discus...

In the paper basic defuzzification techniques are considered. The defuzzification process is present at a fuzzy system when an output fuzzy set should be mapped to a crisped value. Features are given which are the base for a defuzzification techniques comparison. Techniques are classified into several groups. The overview of defuzzification techniques is given, as well as their comparison on th...

Evolutionary Adaptive Defuzzification Methods are a kind of defuzzification methods based on using a parametrical defuzzification expression tuned with evolutionary algorithms. Their goal is to increase the accuracy of the fuzzy system without loosing its interpretability. They induce a kind of rule cooperation in the defuzzification interface. 1 This paper deals with Evolutionary Adaptive Defu...

Defuzzification is the process of converting a fuzzy quantity to precise quantity, just as fuzzification is the conversion of a precise quantity to a fuzzy quantity. Various types of defuzzification methods, are available for conversion of fuzzy to non-fuzzy. In this paper, defuzzification functions in intuitionistic fuzzy environment such as triangular, trapezoidal, L-trapezoidal, R-trapezoida...

A novel technique of designing application specific defuzzification strategies with neural learning is presented. The proposed neural architecture considered as a universal defuzzification approximator is validated by showing the convergence when approximating several existing defuzzification strategies. The method is successfully tested with fuzzy controlled reverse driving of a model truck. T...

Defuzzification converts the final fuzzy output set of fuzzy controller and fuzzy inference systems to a significant crisp value. However, there are various mathematical methods for defuzzification, but there is not any certain systematic method for choosing the best strategy. In this paper, first we explain the structure of a fuzzy inference system and then after a short review of defuzzificat...

Defuzzification is one of the fundamental steps in the development of fuzzy knowledge based systems. Given a fuzzy set μ over the reference set X, defuzzification applied to μ returns an element of X. While a large number of methods exists for the case of X being a numerical scale, only few methods are applicable when X corresponds to a categorical scale. Aggregation procedures have been extens...

AbstractIn general, expert rules expressed by imprecise (fuzzy) words of natural language like “small” lead to control recommendations. If we want design an automatic controller, need, based on these fuzzy recommendations, generate a single value. A procedure for such generation is known as defuzzification. The most widely used defuzzification centroid defuzzification, in which, the desired val...

This paper presents circular polar coordinates transformation of periodic fuzzy membership function. The purpose is identification of domain of periodic membership functions in consequent part of IF-THEN rules. Proposed methods in this paper remove complicatedness concerning domain of periodic membership function from defuzzification in fuzzy approximate reasoning. Defuzzification on circular p...

The starting point of the paper presented are the well-known defuzzification procedures on the one hand and approaches to axiomatize the concept of defuzzification, on the other hand. We present a new attempt to build up an axiomatic foundation for defuzzification theory using the theory of groups and the theory of partially ordered sets, and in particular, the theory of GALOIS connections.