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DOI Prefix: 10.47001/IRJIET

Artificial Intelligence Forecasting Of Total Fertility Rate (TFR) In Ghana

Dr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweTatenda. A. CHIHOHOIndependent Health Economist, ZimbabweThabani NYONISAGIT Innovation Center, Harare, Zimbabwe

Vol 5 No 8 (2021): Volume 5, Issue 8, August 2021 | Pages: 420-423

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 24-09-2021

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Abstract
In this research article, the ANN approach was applied to analyze TFR in Ghana. The employed annual data covers the period 1960-2018 and the out-of-sample period ranges over the period 2019-2030. The residuals and forecast evaluation criteria (Error, MSE and MAE) of the applied model indicate that the model is stable in forecasting TFR in Ghana. The results of the study indicate that annual total fertility rates in Ghana are likely to rise from approximately 4.0 births per woman in 2019 to nearly 6.2 births per woman by 2030. Therefore, the authorities in Ghana should concentrate on addressing adolescents and young adult challenges in accessing sexual and reproductive health (SRH) services, and channel more resources towards women empowerment.
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Citation of this Article

Dr. Smartson. P. NYONI, Tatenda. A. CHIHOHO, Thabani NYONI, “Artificial Intelligence Forecasting Of Total Fertility Rate (TFR) In Ghana” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 8, pp 420-423, August 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.508094
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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