Fuzzy rule based systems have been very popular in many engineering applications. In petroleum engineering, fuzzy rules are normally constructed using some fuzzy rule extraction techniques to establish the petrophysical properties prediction model. However, when generating fizzy rules from the available information, it may result in a sparse fuzzy rule base. The use of more than one input varia...

This paper investigates existence and uniqueness results for the first order fuzzy integro-differential equations. Then numerical results and error bound based on the left rectangular quadrature rule, trapezoidal rule and a hybrid of them are obtained. Finally an example is given to illustrate the performance of the methods.

The ‘hnique selling point” of fuzzy systems is usually the interpretability of its rule base. However, very often only the U C C U T U C ~ of the rule base is measured and used to compare a fuzzy system to other solutions. We have suggested an index to measurz the interpretability of fuzzy rule bases for classification problems. However, the index can be used to describe the interpretability of...

Fuzzy model-based adaptive control, unlike traditional fuzzy control, extracts expert knowledge from data by using model identification techniques. In this paper, we propose an analysis of the contradiction in this knowledge as an additional search criterion during the model identification process. In order to do so, we first define a measure of contradiction between fuzzy rules. Then, we assum...

This paper presents the fuzzy expert system for intelligent support of decision making about cause of stone construction crack of building. The system is based on some linguistic expert expressions formalised by 9 fuzzy knowledge bases. Tuning of fuzzy rules by genetic algorithms provided a good concordance between real causes of cracks and results of decision making by the system.

This paper is an attempt at providing a fuzzy set-based formalization of case-based reasoning. The proposed approach, which does not take into account the learning aspects of case-based reasoning, assumes a principle stating that "the more similar are the problem description attributes, the more similar are the outcome attributes". A weaker form of this principle concluding only on the graded p...

Fuzzy associative memories (FAMs) can be used as a powerful tool for implementing fuzzy rule-based systems. The insight that FAMs are closely related to mathematical morphology (MM) has recently led to the development of new fuzzy morphological associative memories (FMAMs), in particular implicative fuzzy associative memories (IFAMs). As the name FMAM indicates, these models belong to the class...

A special fuzzy modeling method for developing multi-variable fuzzy models on the basis of measured input and output data is presented. Forming the crucial point in fuzzy modeling, the fuzzy model identiication procedure is carried out by applying a special clustering method, the fuzzy c-elliptotypes method, to provide the parameters of the fuzzy model. To enhance the eeciency of the fuzzy mode...

A special fuzzy modeling method for developing multi-variable fuzzy models on the basis of measured input and output data is presented. Representing the crucial point in fuzzy modeling, the fuzzy model identiication procedure is carried out by applying a special clustering method, the fuzzy c-elliptotypes method, providing the parameters of the fuzzy model. To enhance the eeciency of the fuzzy ...