In this paper, the method of least squares is applied to the fuzzy inference rules. We begin studying the conditions in which from a fuzzy set we can build another through the method of least squares. Then we apply ...

A computational model for a fuzzy coprocessor (types and structures of data and the set of instructions) is proposed. The coprocessor will be charged only of the typical operations of fuzzy logic as calculating membership ...

The basic tool considered in this paper is the so-called "graded set", defined on the analogy of the family of α-cuts of a fuzzy set. It is also considered the corresponding extensions of the concepts of a point ...

The aim of this paper is to study a special type of fuzzy relations, the α-equivalences, as well as to consider the relation that connects these with the family of ε-partitions of the referential. Some classic equivalences ...

In this paper we study two ways of generating multi-dimensional aggregation functions. First of all we obtain multi-dimensional OWA operators in two different ways, one of them through quantifiers and the other through ...

The aim of this paper is to present and study one important class of divergence measure between fuzzy subsets, and one important class of divergence measure between fuzzy partitions, each of them having some specific ...

This paper describes the design and development of a sensor based navigation system which makes it possible for a non-holonomous mobile robot to avoid obstacles using information on its environment picked up by a belt of ...

GA-P algorithms combine genetic programming and genetic algorithms to solve symbolic regression problems. In this work, we will learn a model by means of an interval GA-P procedure which can use precise or imprecise examples. ...

In previous works, we have presented two methodologies to obtain fuzzy rules in order to describe the behaviour of a system. We have used Artificial Neural Netorks (ANN) with the {\it Backpropagation} algorithm, and a set ...