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Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm

Model structure selection is a problem in system identification which addresses selecting an adequate model i.e. a model that has a good balance between parsimony and accuracy in approximating a dynamic system. Parameter magnitude-based information criterion 2 (PMIC2), as a novel information criteri...

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Main Authors: Abd Samad, Md Fahmi, Mohd Nasir, Abdul Rahman
Format: Article
Language:English
Published: University of El Oued 2017
Subjects:
Q Science (General)
QA Mathematics
Online Access:http://eprints.utem.edu.my/id/eprint/22715/2/3353-7186-1-PB_MMETIC_JFAS.pdf
http://eprints.utem.edu.my/id/eprint/22715/
http://jfas.info/psjfas/index.php/jfas/article/view/3353/1892
http://dx.doi.org/10.4314/jfas.v9i7s.54
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spelling my.utem.eprints.227152021-09-06T17:11:48Z http://eprints.utem.edu.my/id/eprint/22715/ Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm Abd Samad, Md Fahmi Mohd Nasir, Abdul Rahman Q Science (General) QA Mathematics Model structure selection is a problem in system identification which addresses selecting an adequate model i.e. a model that has a good balance between parsimony and accuracy in approximating a dynamic system. Parameter magnitude-based information criterion 2 (PMIC2), as a novel information criterion, is used alongside Akaike information criterion (AIC). Genetic algorithm (GA) as a popular search method, is used for selecting a model structure. The advantage of using GA is in reduction of computational burden. This paper investigates the identification of dynamic system in the form of NARX (Non-linear AutoRegressive with eXogenous input) model based on PMIC2 and AIC using GA. This shall be tested using computational software on a number of simulated systems. As a conclusion, PMIC2 is able to select optimum model structure better than AIC. University of El Oued 2017 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/22715/2/3353-7186-1-PB_MMETIC_JFAS.pdf Abd Samad, Md Fahmi and Mohd Nasir, Abdul Rahman (2017) Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm. Journal Of Fundamental And Applied Sciences, 9 (7S). pp. 584-599. ISSN 1112-9867 http://jfas.info/psjfas/index.php/jfas/article/view/3353/1892 http://dx.doi.org/10.4314/jfas.v9i7s.54
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic Q Science (General)
QA Mathematics
spellingShingle Q Science (General)
QA Mathematics
Abd Samad, Md Fahmi
Mohd Nasir, Abdul Rahman
Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm
description Model structure selection is a problem in system identification which addresses selecting an adequate model i.e. a model that has a good balance between parsimony and accuracy in approximating a dynamic system. Parameter magnitude-based information criterion 2 (PMIC2), as a novel information criterion, is used alongside Akaike information criterion (AIC). Genetic algorithm (GA) as a popular search method, is used for selecting a model structure. The advantage of using GA is in reduction of computational burden. This paper investigates the identification of dynamic system in the form of NARX (Non-linear AutoRegressive with eXogenous input) model based on PMIC2 and AIC using GA. This shall be tested using computational software on a number of simulated systems. As a conclusion, PMIC2 is able to select optimum model structure better than AIC.
format Article
author Abd Samad, Md Fahmi
Mohd Nasir, Abdul Rahman
author_facet Abd Samad, Md Fahmi
Mohd Nasir, Abdul Rahman
author_sort Abd Samad, Md Fahmi
title Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm
title_short Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm
title_full Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm
title_fullStr Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm
title_full_unstemmed Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm
title_sort discrete-time system identification based on novel information criterion using genetic algorithm
publisher University of El Oued
publishDate 2017
url http://eprints.utem.edu.my/id/eprint/22715/2/3353-7186-1-PB_MMETIC_JFAS.pdf
http://eprints.utem.edu.my/id/eprint/22715/
http://jfas.info/psjfas/index.php/jfas/article/view/3353/1892
http://dx.doi.org/10.4314/jfas.v9i7s.54
_version_ 1710679435369250816
score 13.211869

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