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Comparison Of Information Criterion On Identification Of Discrete-Time Dynamic System

Information criterion is an important factor for model structure selection in system identification. It is used to determine the optimality of a particular model structure with the aim of selecting an adequate model. A good information criterion not only evaluate predictive accuracy but also the par...

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Main Authors: Abd Samad, Md Fahmi, Mohd Nasir, Abdul Rahman
Format: Article
Language:English
Published: Medwell Publishing 2017
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.utem.edu.my/id/eprint/20854/2/5660-5665.pdf
http://eprints.utem.edu.my/id/eprint/20854/
http://docsdrive.com/pdfs/medwelljournals/jeasci/2017/5660-5665.pdf
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spelling my.utem.eprints.208542021-09-06T16:17:49Z http://eprints.utem.edu.my/id/eprint/20854/ Comparison Of Information Criterion On Identification Of Discrete-Time Dynamic System Abd Samad, Md Fahmi Mohd Nasir, Abdul Rahman T Technology (General) TA Engineering (General). Civil engineering (General) Information criterion is an important factor for model structure selection in system identification. It is used to determine the optimality of a particular model structure with the aim of selecting an adequate model. A good information criterion not only evaluate predictive accuracy but also the parsimony of model. There are many information criterions those are widely used such as Akaike Information Criterion (AIC) corrected Akaike Information Criterion (AICc) and Bayesian Information Criterion (BIC). Another information criterion suggesting use of logarithmic penalty, named as Parameter Magnitude-based Information Criterion (PMIC) was also introduced. This study presents a study on comparison between AIC, AICc, BIC and PMIC in selecting the correct model structure for simulated models. This shall be tested using computational software on a number of simulated systems in the form of discrete-time models of various lag orders and number of term/variables. As a conclusion, PMIC performed in optimum model structure selection better than AIC, AICc and BIC. Medwell Publishing 2017 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/20854/2/5660-5665.pdf Abd Samad, Md Fahmi and Mohd Nasir, Abdul Rahman (2017) Comparison Of Information Criterion On Identification Of Discrete-Time Dynamic System. Journal of Engineering and Applied Sciences, 12 (1 SI). pp. 5660-5665. ISSN 1816-949X http://docsdrive.com/pdfs/medwelljournals/jeasci/2017/5660-5665.pdf 10.36478/jeasci.2017.5660.5665
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 T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
Abd Samad, Md Fahmi
Mohd Nasir, Abdul Rahman
Comparison Of Information Criterion On Identification Of Discrete-Time Dynamic System
description Information criterion is an important factor for model structure selection in system identification. It is used to determine the optimality of a particular model structure with the aim of selecting an adequate model. A good information criterion not only evaluate predictive accuracy but also the parsimony of model. There are many information criterions those are widely used such as Akaike Information Criterion (AIC) corrected Akaike Information Criterion (AICc) and Bayesian Information Criterion (BIC). Another information criterion suggesting use of logarithmic penalty, named as Parameter Magnitude-based Information Criterion (PMIC) was also introduced. This study presents a study on comparison between AIC, AICc, BIC and PMIC in selecting the correct model structure for simulated models. This shall be tested using computational software on a number of simulated systems in the form of discrete-time models of various lag orders and number of term/variables. As a conclusion, PMIC performed in optimum model structure selection better than AIC, AICc and BIC.
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 Comparison Of Information Criterion On Identification Of Discrete-Time Dynamic System
title_short Comparison Of Information Criterion On Identification Of Discrete-Time Dynamic System
title_full Comparison Of Information Criterion On Identification Of Discrete-Time Dynamic System
title_fullStr Comparison Of Information Criterion On Identification Of Discrete-Time Dynamic System
title_full_unstemmed Comparison Of Information Criterion On Identification Of Discrete-Time Dynamic System
title_sort comparison of information criterion on identification of discrete-time dynamic system
publisher Medwell Publishing
publishDate 2017
url http://eprints.utem.edu.my/id/eprint/20854/2/5660-5665.pdf
http://eprints.utem.edu.my/id/eprint/20854/
http://docsdrive.com/pdfs/medwelljournals/jeasci/2017/5660-5665.pdf
_version_ 1710679432396537856
score 13.211869

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