Automated Extraction of Fuzzy IF-THEN Rules Using Neural Networks

A Neural Expert System with Automated Extraction of Fuzzy If-Then Rules

This paper proposes ajuzzy neural expert system (FNES) with the following two functions: (1) Generalization of the information derived from the training data and embodiment of knowledge in the form of the fuzzy neural network; (2) Extraction of fuzzy If-Then rules with linguistic relative importance of each proposition in an antecedent (I f -part) from a trained neural network. This paper also ...

RBF Networks Versus Fuzzy If - Then Rules

A Neural Expert System with Automated Extraction of Fuzzy If-Then Rules and Its Application to Medical Diagnosis

This paper proposes ajuzzy neural expert system (FNES) with the following two functions: (1) Generalization of the information derived from the training data and embodiment of knowledge in the form of the fuzzy neural network; (2) Extraction of fuzzy If-Then rules with linguistic relative importance of each proposition in an antecedent (I f -part) from a trained neural network. This paper also ...

Logical structure of fuzzy IF-THEN rules

This paper provides a logical basis for manipulation with fuzzy IF-THEN rules. Our theory is wide enough and it encompasses not only finding a conclusion by means of the compositional rule of inference due to Lotfi A. Zadeh but also other kinds of approximate reasoning methods, e.g. perception-based deduction, provided that there exists a possibility to characterize them within a formal logical...

Optimization under fuzzy if-then rules

The aim of this paper is to introduce a novel statement of fuzzy mathematical programming problems and to provide a method for findig a fair solution to these problems. Suppose we are given a mathematical programming problem in which the functional relationship between the decision variables and the objective function is not completely known. Our knowledge-base consists of a block of fuzzy if-t...