Zabiri, H. and Ramasamy, M. and Lemma, T.D. and Maulud, A. (2011) Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems. In: UNSPECIFIED.
Full text not available from this repository.Abstract
In this paper the integration of linear and nonlinear models in parallel for nonlinear system identification is investigated. A residuals-based sequential identification algorithm using parallel integration of linear Orthornormal basis filters (OBF) and a nonlinear feedforward (MLP) NN model is used and applied to the nonlinear Van de Vusse reactor. Results show improved extrapolation capability of the proposed method in comparison to conventional MLP NN, and opens up a promising area for further research and analysis. © 2011 ENGINEERS AUSTRALIA & AUSTRALIAN OPTICAL.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Additional Information: | cited By 2; Conference of 1st Australian Control Conference, AUCC 2011 ; Conference Date: 10 November 2011 Through 11 November 2011; Conference Code:88164 |
| Uncontrolled Keywords: | Feed-Forward; Identification algorithms; Non-linear model; Parallel integration; Research and analysis, Algorithms; Extrapolation; Identification (control systems); Integration; Nonlinear systems, Neural networks |
| Depositing User: | Mr Ahmad Suhairi UTP |
| Date Deposited: | 09 Nov 2023 15:49 |
| Last Modified: | 09 Nov 2023 15:49 |
| URI: | https://khub.utp.edu.my/scholars/id/eprint/1780 |
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