A comparison between the ARIMA model and neural networks average death in Iraq for the period (1980-2028)

Document Type : Research Paper

Authors

1 Faculty of Nursing, National University of Science and Technology, Thi-Qar, Iraq

2 Mazaya University College, Nasiriyah, Iraq

Abstract

 In this research, the (Box-Jenkins) methodology and 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.

Keywords

[1] K.K.S. Al-Satori and B.M.A. Al-Hiti, Using ARIMA models to predict the money supply for Qatar, Anbar Univ. J. Econ. Administrat. Sci. 35 (2010), 58–83.
[2] M. Hajji, International trade in technology, J. Econ. 5 (1975), no. 57.
[3] H.B.A.-A. Mazouzi and A. Al-Mu’tar, Prediction of the use of artificial neural networks, Doctoral diss. Ahmed Deraya-Adrar University, 2018.
[4] S.M.A. Mustafa, Using ARIMA models and artificial neural networks in predicting the Egyptian stock exchange index EGX30, J. Financ. Commercial Res. 18 (2017), no. 1, 392–416.
[5] S.A.-K. Tumo, Using time series download for predicting people with malignant diseases in Anbar governorate, Anbar Univ. J. Econ. Sci. (2012), no. 8.

Articles in Press, Corrected Proof
Available Online from 27 November 2025
  • Receive Date: 13 January 2023
  • Accept Date: 11 February 2023