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

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

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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.

Item Type: Article
Uncontrolled Keywords: Akaike information criterion, Bayesian information criterion, model structure selection, parameter magnitude-based information criterium, system, software
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Mechanical Engineering
Depositing User: Nor Aini Md. Jali
Date Deposited: 15 May 2018 09:18
Last Modified: 06 Sep 2021 16:17
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