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DOI Prefix: 10.47001/IRJIET

Demonstrating Use of Machine Learning in the Detection of Adolescent Fertility for the Kingdom of Eswatini

Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweThabani NYONIIndependent Researcher & Health Economist, Harare, Zimbabwe

Vol 6 No 12 (2022): Volume 6, Issue 12, December 2022 | Pages: 248-251

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 16-03-2023

doi Logo doi.org/10.47001/IRJIET/2022.612047

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Abstract

This study uses annual time series data on adolescent fertility rate for Eswatini from 1960 to 2020 to predict future trends of adolescent fertility rate over the period 2021 to 2030. The forecast evaluation criteria of the applied model indicate that the ANN (12, 12, 1) model is stable in forecasting adolescent fertility rate. The neural network model projections revealed adolescent fertility will hover around 73 births per 1000 women aged 15-19 throughout the out of sample period. Therefore, we encourage the Kingdom of Eswatini to focus on improving the accessibility and affordability of sexual and reproductive health services among adolescents, strictly enforce laws that protect sexual and reproductive health rights of adolescent girls and women, and fund empowerment programs for youths.

Keywords

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Citation of this Article

Smartson. P. NYONI, Thabani NYONI, “Demonstrating Use of Machine Learning in the Detection of Adolescent Fertility for the Kingdom of Eswatini” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 6, Issue 12, pp 248-251, December 2022. Article DOI https://doi.org/10.47001/IRJIET/2022.612047
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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