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DOI Prefix: 10.47001/IRJIET

Prediction of Art Coverage in Togo Using Artificial Neural Networks

Dr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweThabani NYONIDepartment of Economics, University of Zimbabwe, Harare, Zimbabwe

Vol 5 No 3 (2021): Volume 5, Issue 3, March 2021 | Pages: 105-109

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 31-03-2021

doi Logo doi.org/10.47001/IRJIET/2021.503019

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Abstract
In this research article, the ANN approach was applied to analyze ART coverage in Togo. The employed data covers the period 2000-2018 and the out-of-sample period ranges over the period 2019-2023. The residuals and forecast evaluation criteria (Error, MSE and MAE) of the applied model indicate that the model is stable in forecasting ART coverage in Togo. The results of the study indicate that ART coverage will be around 62 % over the period 2019-2023.The government is encouraged to create more demand for HIV testing & ART services, strengthen TB/HIV collaboration and improve ART access for key populations.
Keywords

ANN, ART coverage, Forecasting.


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, “Prediction of Art Coverage in Togo Using Artificial Neural Networks” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 3, pp 105-109, March 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.503019

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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