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DOI: 10.14569/IJACSA.2021.01212114
PDF

New SARIMA Approach Model to Forecast COVID-19 Propagation: Case of Morocco

Author 1: Ibtissam CHOUJA
Author 2: Sahar SAOUD
Author 3: Mohamed SADIK

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 12, 2021.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: The aim of this paper is to avoid any future health crises by analysing COVID-19 data of Morocco using Time Series to get more information about how the pandemic is spreading. For this reason, we used a statistical model called Seasonal Autoregressive Integrated Moving Average (SARIMA) to forecast the new confirmed cases, new deaths, cumulative cases and deaths. Besides predicting the spreading of COVID-19, this study will also help decision makers to better take the right decisions at the right time. Finally, we evaluated the performance of our model by measuring metrics such as Mean Squared Error (MSE). We have applied our SARIMA model for a forward forecasting in a period of 50 days, the MSE reported was 62196.46 for cumulative cases forecasting, and 621.14 for cumulative deaths forecasting.

Keywords: COVID-19, machine learning, seasonal autoregres-sive integrated moving average, SARIMA, statistical modeling, time series forecasting

Ibtissam CHOUJA, Sahar SAOUD and Mohamed SADIK, “New SARIMA Approach Model to Forecast COVID-19 Propagation: Case of Morocco” International Journal of Advanced Computer Science and Applications(IJACSA), 12(12), 2021. http://dx.doi.org/10.14569/IJACSA.2021.01212114

@article{CHOUJA2021,
title = {New SARIMA Approach Model to Forecast COVID-19 Propagation: Case of Morocco},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.01212114},
url = {http://dx.doi.org/10.14569/IJACSA.2021.01212114},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {12},
author = {Ibtissam CHOUJA and Sahar SAOUD and Mohamed SADIK}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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