- Tytuł:
- A fuzzy neural network for knowledge acquisition in complex time series
- Autorzy:
-
Kasabov, N.
Kim, J.
Kozma, R. - Powiązania:
- https://bibliotekanauki.pl/articles/205889.pdf
- Data publikacji:
- 1998
- Wydawca:
- Polska Akademia Nauk. Instytut Badań Systemowych PAN
- Tematy:
-
logika rozmyta
sieć neuronowa rozmyta
układ dynamiczny
adaptation
computational neural net
fuzzy logic
fuzzy neural net
knowledge acquisition
time-series and dynamical system - Opis:
- A novel fuzzy neural network, called FuNN, is applied here for time-series modeling. FuNN models have several features that make them well suited to a wide range of knowledge engineering applications. These strengths include fast and accurate learning, good generalisation capabilities, excellent explanation facilities in the form of semantically meaningful fuzzy rules, and the ability to accomodate both numerical data and existing expert knowledge about the problem under consideration. We investigate the effectiveness of the proposed neuro-fuzzy hybrid architectures for manipulating the future behaviour of nonlinear dynamical systems and interpreting fuzzy if-then rules. A well-known example of Box and Jenkins is used as a benchmark time series in the proposed modelling approach and the other modelling approach. Finally, experimental results and comparisons with the other popular neuro-fuzzy inference system, namely Adaptive Network-based Fuzzy Inference System (ANFIS) are also presented.
- Źródło:
-
Control and Cybernetics; 1998, 27, 4; 593-611
0324-8569 - Pojawia się w:
- Control and Cybernetics
- Dostawca treści:
- Biblioteka Nauki
Artykuł