Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems
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) N...
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2011
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my.utp.eprints.107482013-12-16T23:48:36Z Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems H., Zabiri M., Ramasamy Lemma D, Tufa Maulud, Abdulhalim TP Chemical technology 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 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/10748/1/HZabiri_aucc2011.pdf http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6114303&tag=1 H., Zabiri and M., Ramasamy and Lemma D, Tufa and Maulud, Abdulhalim (2011) Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems. In: Australian Control Conference (AUCC), 2011 , 10-11 Nov. 2011 , Melbourne, Australia. http://eprints.utp.edu.my/10748/ |
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TP Chemical technology H., Zabiri M., Ramasamy Lemma D, Tufa Maulud, Abdulhalim Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems |
| description |
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. |
| format |
Conference or Workshop Item |
| author |
H., Zabiri M., Ramasamy Lemma D, Tufa Maulud, Abdulhalim |
| author_facet |
H., Zabiri M., Ramasamy Lemma D, Tufa Maulud, Abdulhalim |
| author_sort |
H., Zabiri |
| title |
Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems
|
| title_short |
Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems
|
| title_full |
Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems
|
| title_fullStr |
Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems
|
| title_full_unstemmed |
Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems
|
| title_sort |
integrated obf-nn models for extrapolation enhancement in conventional neural networks for nonlinear systems |
| publishDate |
2011 |
| url |
http://eprints.utp.edu.my/10748/1/HZabiri_aucc2011.pdf http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6114303&tag=1 http://eprints.utp.edu.my/10748/ |
| _version_ |
1738655892298006528 |