<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Digital technologies such as the Internet, big data, cloud computing, mobile communication, and artificial intelligence have played an important role in the prevention and control of this new crown epidemic. Driven by big data technology, collaborative governance in the digital era has injected new dynamics for collaborative governance in the general sense, especially in this new crown epidemic prevention and control shows a different governance logic from the past, and the refinement and extraction of this governance logic is the key to enhance the ability of new crown epidemic prevention and control. Compared with the previous model in which a single governmental governance body played a role. In this paper, the necessity of building a big data analysis system is clarified by analyzing the limitations of the data analysis means of the existing trip code system. The overall epidemic prevention advantage of adopting the big data trip code policy has increased by 51.95% for regions with high crisis risk level and strong economic power, such as Guangdong, Zhejiang and Shanghai, which need to face the risk spread from domestic and imported risks under the big data trip code control, the increase of new cases compared to the previous comparison has decreased by 68.5%, which can visually see the big data trip code epidemic prevention We can visually see the effectiveness of big data trip codes in preventing the epidemic and making excellent contributions to the global fight against the epidemic.</p>
</abstract>

Digital technologies such as the Internet, big data, cloud computing, mobile communication, and artificial intelligence have played an important role in the prevention and control of this new crown epidemic. Driven by big data technology, collaborative governance in the digital era has injected new dynamics for collaborative governance in the general sense, especially in this new crown epidemic prevention and control shows a different governance logic from the past, and the refinement and extraction of this governance logic is the key to enhance the ability of new crown epidemic prevention and control. Compared with the previous model in which a single governmental governance body played a role. In this paper, the necessity of building a big data analysis system is clarified by analyzing the limitations of the data analysis means of the existing trip code system. The overall epidemic prevention advantage of adopting the big data trip code policy has increased by 51.95% for regions with high crisis risk level and strong economic power, such as Guangdong, Zhejiang and Shanghai, which need to face the risk spread from domestic and imported risks under the big data trip code control, the increase of new cases compared to the previous comparison has decreased by 68.5%, which can visually see the big data trip code epidemic prevention We can visually see the effectiveness of big data trip codes in preventing the epidemic and making excellent contributions to the global fight against the epidemic.

Study of trip card data analysis system under big data

Institute for Nationalities Attached to Hebei Normal University

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Study of trip card data analysis system under big data"}

Digital technologies such as the Internet, big data, cloud computing, mobile communication, and artificial intelligence have played an important role in the...

Study of trip card data analysis system under big data

Online veröffentlicht: 07. Juni 2023

Seitenbereich: -

Eingereicht: 27. Juli 2022

Akzeptiert: 13. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00372

Schlüsselwörter
New crown epidemic, Trip card, Big data SNE algorithm, Information pre-grouping, Robustness test

© 2023 Manman Sun et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Study of trip card data analysis system under big data

Online veröffentlicht: 07. Juni 2023

Seitenbereich: -

Eingereicht: 27. Juli 2022

Akzeptiert: 13. Dez. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00372

SchlüsselwörterNew crown epidemic, Trip card, Big data SNE algorithm, Information pre-grouping, Robustness test

© 2023 Manman Sun et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
New crown epidemic, Trip card, Big data SNE algorithm, Information pre-grouping, Robustness test