We develop, based upon the mountain clustering method, a procedure for learning fuzzy
systems models from data. First we discuss the mountain clustering method. We then show …

Self-organizing maps (SOM) have proven to be of significant economic value in the areas of
finance, economic and marketing applications. As a result, this area is rapidly becoming a …

The authors propose an automatic fuzzy system design method that uses a genetic
algorithm and integrates three design stages. The method determines membership …

The advent of the computer age has set in motion a profound shift in our perception of
science-its structure, its aims and its evolution. Traditionally, the principal domains of …

This paper presents different approaches to the problem of fuzzy rules extraction by using
fuzzy clustering as the main tool. Within these approaches we describe six methods that …

The aim of this article is to present a new approach to machine learning (precisely in
classification problems) in which the use of fuzzy logic has been taken into account. We …

The paper deals with a new approach to the learning of fuzzy rules. It suggests a solution to
one of the problems of crucial importance for the learning of fuzzy rules by back propagation …

The problem of generating desirable fuzzy rules is very important in the development of
fuzzy systems. The purpose of this paper is to present a generation method of fuzzy control …

The elevator group control systems are the control systems that manage systematically,
three or more elevators in order to efficiently transport the passengers. In the elevator group …

The genetic algorithms are probabilistic algorithms which start with an initial population of
likely problem solutions, and then evolve towards better solutions. This work proposes a …