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Ashraf M Shareef
Statistics Department, Administration and Economics College, Sumer University, Iraq
Medicine & Pharmacology Public Health

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A Comparison Between the ARIMA Model and Neural Networks Average Death in Iraq for the Period (1980-2018): Perbandingan Antara Model ARIMA dan Jaringan Syaraf Tiruan Rata-rata Kematian di Irak untuk Periode (1980-2018) Ashraf M Shareef; Sarmad Jaafar Naser
Academia Open Vol. 9 No. 2 (2024): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.9.2024.10409

Abstract

In this research, the (Box-Jenkins) methodology and annual artificial neural networks in predicting theoretical and practical levels were identified and clarified by constructing time series models and artificial networks to predict the mortality rate of Iraq and the data represented by the mortality rate for the time period (1980-2028). It was obtained from the Central Statistical Organization where the data were analyzed using time series according to the Box-Jenkins method and artificial neural networks using the program (Eviws.v9, SPSS, Zaitun.TS) and the most important conclusions and recommendations were reached, the most important of which proved the time series model using residues and values The ARMA model has its advantage over the neural network model for predicting Iraqi mortality. So we recommend using this form. Highights: Utilized Box-Jenkins and neural networks for mortality prediction (1980–2028). Data analyzed using EViews, SPSS, Zaitun.TS, with ARMA outperforming neural networks. Recommended ARMA model for accurate Iraqi mortality rate forecasting. Keywords: Box-Jenkins, Neural Networks, Prediction, ARIMA model, Death in Iraq
Co-Authors Sarmad Jaafar Naser