Hansun, Seng and Charles, Vincent and Gherman, Tatiana and Indrati, Christiana Rini and , Subanar, , Subanar (2021) A tuned Holt-Winters white-box model for COVID-19 prediction. International Journal of Management and Decision Making, 20 (3).
Full text not available from this repository.Abstract
The year 2020 has become memorable the moment the novel COVID-19 spread massively around the world to become a pandemic. In this paper, we analyse and predict the future trend of the COVID-19 cases for the top ten countries with the highest number of confirmed cases to date and the top ten countries with the highest growth percentage within the last month. Since many recent works have proposed that the COVID-19 pattern follows an exponential distribution, we use a tuned approach to the Holt-Winters' additive method as a white-box model. Based on the analysis, we found that most of the countries are still presenting an increasing trend of confirmed cases in the near future. Apart from vaccine and drug development, measures such as vigilance, strategic governmental actions, public awareness, and social distancing are unarguably continuously needed to handle the spreading of COVID-19 and avoid or curb the next wave of the outbreak.
| Item Type: | Article |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 21 Oct 2021 02:43 |
| Last Modified: | 21 Oct 2021 02:43 |
| URI: | https://kc.umn.ac.id/id/eprint/18920 |
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