Creator:

Czabański, Robert

Contributor:

Beliczyński, Bartłomiej - red.

Title:

Neuro-fuzzy modelling based on a deterministic annealing approach

Subtitle:

Intelligent Control and Signal Processing

Group publication title:

AMCS, Volume 15 (2005)

Subject and Keywords:

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.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2005

Resource Type:

artykuł

Pages:

561-576

Source:

AMCS, Volume 15, Number 4 (2005) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego