Multi-objective optimization of NARX model for system identification using genetic algorithm
The problem of constructing an adequate and parsimonious Nonlinear Autoregressive model process with eXogenous input (NARX) structure for modeling nonlinear dynamic system is studied. NARX has been shown to perform function approximation and represent dynamic systems. The structures are usually gues...
| Main Authors: | , , |
|---|---|
| Format: | Book Section |
| Published: |
Institute of Electrical and Electronics Engineers
2009
|
| Subjects: |
| _version_ | 1796855173123932160 |
|---|---|
| author | Loghmanian, S. Mohammad Reza Ahmad, Robiah Jamaluddin , Hishamuddin |
| author_facet | Loghmanian, S. Mohammad Reza Ahmad, Robiah Jamaluddin , Hishamuddin |
| author_sort | Loghmanian, S. Mohammad Reza |
| collection | ePrints |
| description | The problem of constructing an adequate and parsimonious Nonlinear Autoregressive model process with eXogenous input (NARX) structure for modeling nonlinear dynamic system is studied. NARX has been shown to perform function approximation and represent dynamic systems. The structures are usually guessed or selected in accordance with the designer prior knowledge, however the multiplicity of the model parameters make it troublesome to get an optimum structure. The trial and error approach is not efficient and may not arrive to an optimum structure. An alternative algorithm based on multi-objective optimization algorithm is proposed. The developed model should fulfill two criteria or objectives namely good predictive accuracy and optimum model structure. The result shows that the proposed algorithm is able to correctly identify the simulated examples and adequately model real data structure and based on a set of solutions called the Pareto optimal set, from which the best network is selected. |
| first_indexed | 2024-03-05T18:24:45Z |
| format | Book Section |
| id | utm.eprints-13001 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T18:24:45Z |
| publishDate | 2009 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | utm.eprints-130012011-07-12T01:11:06Z http://eprints.utm.my/13001/ Multi-objective optimization of NARX model for system identification using genetic algorithm Loghmanian, S. Mohammad Reza Ahmad, Robiah Jamaluddin , Hishamuddin TJ Mechanical engineering and machinery The problem of constructing an adequate and parsimonious Nonlinear Autoregressive model process with eXogenous input (NARX) structure for modeling nonlinear dynamic system is studied. NARX has been shown to perform function approximation and represent dynamic systems. The structures are usually guessed or selected in accordance with the designer prior knowledge, however the multiplicity of the model parameters make it troublesome to get an optimum structure. The trial and error approach is not efficient and may not arrive to an optimum structure. An alternative algorithm based on multi-objective optimization algorithm is proposed. The developed model should fulfill two criteria or objectives namely good predictive accuracy and optimum model structure. The result shows that the proposed algorithm is able to correctly identify the simulated examples and adequately model real data structure and based on a set of solutions called the Pareto optimal set, from which the best network is selected. Institute of Electrical and Electronics Engineers 2009 Book Section PeerReviewed Loghmanian, S. Mohammad Reza and Ahmad, Robiah and Jamaluddin , Hishamuddin (2009) Multi-objective optimization of NARX model for system identification using genetic algorithm. In: 2009 1st International Conference on Computational Intelligence, Communication Systems and Networks, CICSYN 2009. Institute of Electrical and Electronics Engineers, New York, 196 -201. ISBN 978-076953743-6 http://dx.doi.org/10.1109/CICSYN.2009.62 doi:10.1109/CICSYN.2009.62 |
| spellingShingle | TJ Mechanical engineering and machinery Loghmanian, S. Mohammad Reza Ahmad, Robiah Jamaluddin , Hishamuddin Multi-objective optimization of NARX model for system identification using genetic algorithm |
| title | Multi-objective optimization of NARX model for system identification using genetic algorithm |
| title_full | Multi-objective optimization of NARX model for system identification using genetic algorithm |
| title_fullStr | Multi-objective optimization of NARX model for system identification using genetic algorithm |
| title_full_unstemmed | Multi-objective optimization of NARX model for system identification using genetic algorithm |
| title_short | Multi-objective optimization of NARX model for system identification using genetic algorithm |
| title_sort | multi objective optimization of narx model for system identification using genetic algorithm |
| topic | TJ Mechanical engineering and machinery |
| work_keys_str_mv | AT loghmaniansmohammadreza multiobjectiveoptimizationofnarxmodelforsystemidentificationusinggeneticalgorithm AT ahmadrobiah multiobjectiveoptimizationofnarxmodelforsystemidentificationusinggeneticalgorithm AT jamaluddinhishamuddin multiobjectiveoptimizationofnarxmodelforsystemidentificationusinggeneticalgorithm |