Artificial Intelligence Forecasting Of Total Fertility Rate (TFR) In Ghana
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.
Country : Zimbabwe
1 Dr. Smartson. P. NYONI2 Tatenda. A. CHIHOHO3 Thabani NYONI
ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
Independent Health Economist, Zimbabwe
SAGIT Innovation Center, Harare, Zimbabwe
IRJIET, Volume 5, Issue 8, August 2021 pp. 420-423
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