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DOI Prefix: 10.47001/IRJIET
Vol 6 No 12 (2022): Volume 6, Issue 12, December 2022 | Pages: 276-280
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 16-03-2023
This study uses annual time series data on adolescent fertility rate for the Gambia 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 that adolescent fertility rate will decline throughout the out of sample period. Therefore, we encourage the government of Gambia to scale up awareness programs in the community, strictly enforce laws that protect sexual and reproductive health rights for women, channel more funds towards youth empowerment programs and promote girl child education.
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Smartson. P. NYONI, Thabani NYONI, “Demonstrating Use of a Machine Learning Technique in Adolescent Health Policy-Making in the Gambia” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 6, Issue 12, pp 276-280, December 2022. Article DOI https://doi.org/10.47001/IRJIET/2022.612052
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