Autor:

Czabański, Robert

Współtwórca:

Beliczyński, Bartłomiej - red.

Tytuł:

Neuro-fuzzy modelling based on a deterministic annealing approach

Podtytuł:

Intelligent Control and Signal Processing

Tytuł publikacji grupowej:

AMCS, Volume 15 (2005)

Temat i słowa kluczowe:

fuzzy systems ; neural networks ; neuro-fuzzy systems ; rules extraction ; deterministic annealing ; prediction

Abstract:

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-thenrules, which uses a conjunctive as well as a logical interpretation of those rules. In the original approach, the estimationof unknown system parameters was made by means of a combination of both gradient and least-squares methods. Thenovelty of the learning algorithm consists in the application of a deterministic annealing optimization method. It leads to animprovement in the neuro-fuzzy modelling performance. To show the validity of the introduced method, two examples ofapplication concerning chaotic time series prediction and system identification problems are provided.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2005

Typ zasobu:

artykuł

Strony:

561-576

Źródło:

AMCS, Volume 15, Number 4 (2005) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego