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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.
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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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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