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  • In Jour Smart Sensing And Intelligent Systems

 

Research paper | 13-December-2017

SYSTEM IDENTIFICATION OF NONLINEAR AUTOREGRESSIVE MODELS IN MONITORING DENGUE INFECTION

This paper proposes system identification on application of nonlinear AR (NAR) based on Artificial Neural Network (ANN) for monitor of dengue infections. In building the model, three selection criteria, i.e. the final prediction error (FPE), Akaike’s Information Criteria (AIC), and Lipschitz number were used. Each of the models is divided into two approaches, which are unregularized approach and regularized approach. The findings indicate that NARMAX model with regularized approach yields

H. Abdul Rahim, F. Ibrahim, M. N. Taib

International Journal on Smart Sensing and Intelligent Systems, Volume 3 , ISSUE 4, 783–806

Research paper | 13-December-2017

MODEL ORDER SELECTION CRITERION FOR MONITORING HAEMOGLOBIN STATUS IN DENGUE PATIENTS USING ARMAX MODEL

This paper describes the development of linear autoregressive moving average with exogenous input (ARMAX) models to monitor the progression of dengue infection based on hemoglobin status. Three differents ARMAX model order selection criteria namely Final Prediction Error (FPE), Akaike’s Information Criteria (AIC) and Lipschitz number have been evaluated and analyzed. The results showed that Lipschitz number has better accuracy compared to FPE and AIC. Finally based on Lipschitz number

H. Abdul Rahim, F. Ibrahim, M. N. Taib, R. Abdul Rahim, Y.Mad Sam

International Journal on Smart Sensing and Intelligent Systems, Volume 1 , ISSUE 2, 403–419

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