Extraction of fuzzy rules using deterministic annealing integrated with ε-insensitive learning

• Autorzy: Robert Czabański
• Języki publikacji: EN

Abstrakty

EN

A new method of parameter estimation for an artificial neural network inference system based on a logical interpretation of fuzzy if-then rules (ANBLIR) is presented. The novelty of the learning algorithm consists in the application of a deterministic annealing method integrated with ε-insensitive learning. In order to decrease the computational burden of the learning procedure, a deterministic annealing method with a "freezing" phase and ε-insensitive learning by solving a system of linear inequalities are applied. This method yields an improved neuro-fuzzy modeling quality in the sense of an increase in the generalization ability and robustness to outliers. To show the advantages of the proposed algorithm, two examples of its application concerning benchmark problems of identification and prediction are considered.

Słowa kluczowe

EN

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

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2006
• Tom: 16
• Numer: 3
• Strony: 357-372

Daty

wydano

2006

otrzymano

2005-10-04

poprawiono

2006-04-28

Twórcy

autor

Robert Czabański

• Institute of Electronics Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland

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