International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Projecting Under Five Mortality Rate for Turkey Using a Machine Learning Approach

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: 521-524

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/2022.607116

pdf iconFull Text PDF
Abstract

This study uses annual time series data on under five mortality rate (U5MR) for Turkey 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 revealed that annual U5MR will continue to decline over the out of sample period. Therefore, we encourage the Turkish government to address all the factors that significantly affect the successful implementation of the maternal and child health program.

Keywords

ANN, Forecasting, U5MR.


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, “Projecting Under Five Mortality Rate for Turkey Using a Machine Learning Approach” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 6, Issue 7, pp 521-524, July 2022. Article DOI https://doi.org/10.47001/IRJIET/2022.607116

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
References
  1. UNICEF. (2019). Levels and trends in child mortality: report 2019. Estimates developed by the UN Inter-agency Group for child mortality estimation. New York: UNICEF.
  2. United Nations. (2015). transforming our world: The 2030 agenda for sustainable development, A/RES/70/1. New York: UN General Assembly.
  3. UN (2020) sustainable development goals. https://www.un.org/sustainabl development/development-agenda
  4. UNICEF (2018). Every Child alive. New York: UNICEF
  5. World Health Organization (WHO) (2019). SDG 3: Ensure healthy lives and promote wellbeing for all at all ages.
  6. Zhao N., Charland K., Carabali M., Elaine O., Nsoesie., MaheuGiroux M., Rees E., Yuan M., Balaguera C G., Ramirez G J., & Zinszer K (2020). Machine learning and dengue forecasting: Comparing random forests and artificial neural networks for predicting dengue burden at national and sub-national scales in Colombia. PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008056
  7. Panch T., Szolovits P., & Atun R (2018). Artificial intelligence, machine learning and health systems, 5, 2, 020303.
  8. United Nation. Transforming our world: The 2030 agenda for sustainable \development 2016.

Copyright @ 2026 IRJIET. All Right Reserved.

Licensed underCreative Commons Attribution 4.0 International License.