Analyzing Under Five Mortality Rate for Togo Using a Machine Learning Technique

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

Vol 6 No 7 (2022): Volume 6, Issue 7, July 2022 | Pages: 509-512

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 06-09-2022

doi Logo doi.org/10.47001/IRJIET/2022.607113

Abstract
This study uses annual time series data on under five mortality rate (U5MR) for Togo from 1960 to 2020 to predict future trends of U5MR over the period 2021 to 2030. Residuals and forecast evaluation criteria indicate that the applied ANN (12, 12, 1) model is stable in forecasting under five mortality rate. ANN model projections suggest thatU5MR will remain high throughout the out of sample period. Hence, authorities in Togo must address all the major challenges that hinder the successful implementation of the third sustainable development goal (SDG3). 
Keywords

ANN, Forecasting, U5MR


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, “Analyzing Under Five Mortality Rate for Togo Using a Machine Learning Technique” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 6, Issue 7, pp 509-512, July 2022. Article DOI https://doi.org/10.47001/IRJIET/2022.607113

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