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DOI Prefix: 10.47001/IRJIET

Projecting Total Fertility Rates for Jordan Using Artificial Neural Networks

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: 211-215

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 14-09-2021

doi Logo doi.org/10.47001/IRJIET/2021.508044

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Abstract
This study intended to predict total fertility rates (TFR) for Jordan using Artificial Neural Networks from 2019 to 2030. Jordanian data on TFRs from World Bank Online database from 1960 to 2018 was used. Results show that TFRs for Jordan is predicted to slightly increase from 3.2 to 3.4 in 2027 before declining to 3.2 by 2030.
Keywords

ANN, Forecasting, Total fertility rate (TFR).


Citation of this Article

Dr. Smartson. P. NYONI, Tatenda. A. CHIHOHO, Thabani NYONI, “Projecting Total Fertility Rates for Jordan Using Artificial Neural Networks” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 8, pp 211-215, August 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.508044

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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