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DOI Prefix: 10.47001/IRJIET

Forecasting Infant Mortality Rate in Sierra Leone Using Artificial Neural Networks

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: 597-601

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/2021.503102

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Abstract
In this research work, the ANN approach was applied to analyze infant mortality rate in Sierra Leone. The employed annual 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 infant mortality rate in Sierra Leone. The ANN (12, 12, 1) model predictions suggest that IMR will remain very high in the out-of-sample period. The government is therefore encouraged to allocate more financial resources towards improving health infrastructure especially for primary health care, increasing coverage for child vaccinations and facility based deliveries.
Keywords

ANN, Forecasting, infant mortality rate.


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, “Forecasting Infant Mortality Rate in Sierra Leone Using Artificial Neural Networks” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 3, pp 597-601, March 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.503102

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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