- Tytuł:
- Neuro-fuzzy modelling based on a deterministic annealing approach
- Autorzy:
- Czabański, R.
- Powiązania:
- https://bibliotekanauki.pl/articles/908442.pdf
- Data publikacji:
- 2005
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
system rozmyty
sieć neuronowa
ekstrakcja reguł
fuzzy systems
neural networks
neuro-fuzzy systems
rules extraction
deterministic annealing
prediction - Opis:
- 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.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2005, 15, 4; 561-576
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł