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All Journal Bulletin of Electrical Engineering and Informatics
Hishamuddin, Siti Najihah
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Electrical & Electronics Engineering

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Covid-19 forecasting model based on machine learning approaches: a review Sayeed, Md Shohel; Hishamuddin, Siti Najihah; Song, Ong Thian
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7304

Abstract

As coronavirus disease (Covid-19) it is a contagious disease that is spread by the SARS-CoV-2 virus, one of the most common causes of disease in humans. The disease was initially discovered in Wuhan, China, in 2019, and has now spread throughout the world, including Malaysia. A large number of people have lost their life partners and families because of this disease. Thus, in order for us to stop this epidemic spread, we have to implement social distance. The Covid-19 infection displays this type of behavior, which necessitates the development of mathematical and predictive modeling techniques capable of predicting possible disease patterns or trends, in order to assist the government and health authorities in predicting and preparing for potential outbreaks. The purpose of this paper is to provide an in-depth critique and analysis of the machine-learning approaches that have been implemented by researchers to predict Covid-19, based on existing research. As a result, future researchers will be able to use this paper as a valuable resource for their research related to the Covid-19 forecasting model.
Co-Authors Sayeed, Md Shohel Song, Ong Thian