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2005 | 15 | 4 | 561-576
Tytuł artykułu

Neuro-fuzzy modelling based on a deterministic annealing approach

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper introduces a new learning algorithm for artificial neural networks, based on a fuzzy inference system ANBLIR. It is a computationally effective neuro-fuzzy system with parametrized fuzzy sets in the consequent parts of fuzzy if-then rules, which uses a conjunctive as well as a logical interpretation of those rules. In the original approach, the estimation of unknown system parameters was made by means of a combination of both gradient and least-squares methods. The novelty of the learning algorithm consists in the application of a deterministic annealing optimization method. It leads to an improvement in the neuro-fuzzy modelling performance. To show the validity of the introduced method, two examples of application concerning chaotic time series prediction and system identification problems are provided.
Rocznik
Tom
15
Numer
4
Strony
561-576
Opis fizyczny
Daty
wydano
2005
otrzymano
2005-03-24
poprawiono
2005-07-12
(nieznana)
2005-08-04
Twórcy
  • Department of Automatic Control, Electronics and Computer Sciences, Silesian University of Technology, ul. Akademicka 16, 44-100Gliwice, Poland
Bibliografia
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Bibliografia
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