Interpolation of fuzzy if-then rules by neural networks

RBF Networks Versus Fuzzy If - Then Rules

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...

Representation of Fuzzy IF-THEN rules by Petri Nets

This article is about visualization of modelling steering and decisional processes described by fuzzy IF-THEN rules modified by Petri Nets.

Continuous genetic algorithm-based fuzzy neural network for learning fuzzy IF-THEN rules

This study proposes a fuzzy neural network (FNN) that can process both fuzzy inputs and outputs. The continuous genetic algorithm (CGA) is employed to enhance its performance. Both the simulation and real-world problem results show that the proposed CGA-based FNN can obtain the relationship between fuzzy inputs and outputs. CGA can not only shorten the training time but also increase the accura...