Prediction model of global COVID-19 based on big data technology

Yingbing Fan; Lina Sun; Xuemei Lu; Xianru Bao

doi:10.1117/12.2636433

6 May 2022 Prediction model of global COVID-19 based on big data technology

Yingbing Fan, Lina Sun, Xuemei Lu, Xianru Bao

Proceedings Volume 12176, International Conference on Algorithms, Microchips and Network Applications; 1217606 (2022) https://doi.org/10.1117/12.2636433
Event: International Conference on Algorithms, Microchips, and Network Applications 2022, 2022, Zhuhai, China

Abstract

In order to overcome the trend influence of novel Coronavirus epidemic in the future, this paper proposes the panel data modeling method based on big data crawler technology, which is based on Python crawler technology to obtain a more effective estimation model from the dynamic perspective of time and cross section. The results showed that the fixed effect error rate established by the development of COVID-19 in China, Japan, South Korea, Germany and Italy was about 3%, and there is a positive correlation between cured cases and confirmed cases of COVID-19. The predicted confirmed cases of COVID-19 in week 63 will be 69, 11,908, 3156, 112293 and 147,545, respectively.

Citation Download Citation

Yingbing Fan, Lina Sun, Xuemei Lu, and Xianru Bao "Prediction model of global COVID-19 based on big data technology", Proc. SPIE 12176, International Conference on Algorithms, Microchips and Network Applications, 1217606 (6 May 2022); https://doi.org/10.1117/12.2636433

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