Titre :
|
A learning procedure to identify weighted rules by neural networks
|
Auteurs :
|
A. Blanco ;
M. Delgado ;
I. Requena
|
Type de document :
|
article/chapitre/communication
|
Année de publication :
|
1995
|
Format :
|
p29-36
|
Langues:
|
= Anglais
|
Catégories :
|
INFORMATIQUE-MESURES
|
Mots-clés:
|
RESEAU DE NEURONES
;
SYSTEME EXPERT
;
LOGIQUE FLOUE
;
APPRENTISSAGE
;
ALGORITHME
|
Résumé :
|
In many cases the identification of systems by means of fuzzy rules is given by taking these rules from a predetermined set of possible ones. In this case, the correct description of the system is to be given by a finite set of rules each with an associated weight which assesses its correctness or accuracy. Here we present a method to learn this consistence level or weight by a neural network. The design of this neural network as well as the features of the training models are discussed. The paper concludes with an example.
|
Source :
|
Fuzzy sets and systems, vol n°69
|