COVID-19 pandemic prediction using machine learning methods

Zifan Hu; Fengxu Liu; Keying Feng; Shijie Xu

doi:10.1117/12.2641012

13 October 2022 COVID-19 pandemic prediction using machine learning methods

Zifan Hu, Fengxu Liu, Keying Feng, Shijie Xu

Proceedings Volume 12287, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022); 122871Y (2022) https://doi.org/10.1117/12.2641012
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022), 2022, Wuhan, China

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.

Citation Download Citation

Zifan Hu, Fengxu Liu, Keying Feng, and Shijie Xu "COVID-19 pandemic prediction using machine learning methods", Proc. SPIE 12287, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022), 122871Y (13 October 2022); https://doi.org/10.1117/12.2641012

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