COVID-19 Pandemic Prediction using Machine Learning Methods
2022 International Conference on Cloud Computing, Performance Computing, and Deep Learning, CCPCDL 2022
; 12287, 2022.
Article
in English
| Scopus | ID: covidwho-2137319
ABSTRACT
In this paper, we aim to predict the cases of covid-19 pandemic according to linear regression model and random forest model. We decide to try to predict the virus using the daily high and low temperatures because it is one of the biggest factors that can affect the spread and death of the virus.we decide to use days_num, vaccine_days, and ma_temp_high as features.Cases and deaths as labels. We find that that the virus surely has some relationship with temperature. If the theory turns out to be true, in the future, adjusting control efforts based on temperature could greatly improve efficiency and save money. Reduce ineffective expenditures and improve the quality of prevention and control. © 2022 SPIE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Prognostic study
Language:
English
Journal:
2022 International Conference on Cloud Computing, Performance Computing, and Deep Learning, CCPCDL 2022
Year:
2022
Document Type:
Article
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