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DOI Prefix: 10.47001/IRJIET

Forecasting Infant Mortality Rate in Togo Using a Machine Learning Algorithm

Dr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweThabani NYONIDepartment of Economics, University of Zimbabwe, Harare, Zimbabwe

Vol 5 No 3 (2021): Volume 5, Issue 3, March 2021 | Pages: 602-607

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 05-04-2021

doi Logo doi.org/10.47001/IRJIET/2021.503103

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Abstract

In this piece of work, the ANN approach was applied to analyze infant mortality rate (IMR) in Togo. The employed data covers the period 1960-2020 and the out-of-sample period ranges over the period 2021-2030. The residuals and forecast evaluation criteria (Error, MSE and MAE) of the applied model indicate that the model is stable in forecasting IMR rate in Togo. The applied ANN (12, 12, 1) model predictions suggest that IMR will be around 44/1000 live births per year in the coming 10 years. Therefore the government should focus on improving the quality of health care services especially primary health care and work towards developing strategies to retain its skilled health labour force.

Keywords

ANN, Forecasting, infant mortality rate.


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, “Forecasting Infant Mortality Rate in Togo Using a Machine Learning Algorithm” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 3, pp 602-606, March 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.503103

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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