EUDoptimizer: Assisting End Users in Composing IF-THEN Rules Through Optimization

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...

Developing Reliable yet Flexible Software through If-Then Model Transformation Rules

Developing reliable yet flexible software is a hard problem. Although modeling methods enjoy a lot of advantages, the exclusive use of just one of them, in many cases, may not guarantee the development of reliable and flexible software. Formal modeling methods ensure reliability because they use a rigorous approach to software development. However, lack of knowledge and high cost practically fo...

Optimization Under Fuzzy If-Then Rules Using Stochastic Algorithms

A new approach to optimization of processes described by fuzzy rules, in which the functional relationship between the decision variables and the objective function is not completely known, is introduced in this paper. It is based on stochastic algorithms and allows to determine optimal values of state variables and to optimize fuzzy rules (parameters of membership functions). Stochastic algori...

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...