Research Article
Study on the Dynamics of Virus Propagation in Combination with Big Data and Kinetic Models
@INPROCEEDINGS{10.1007/978-3-030-67874-6_4, author={Guo-bin Zeng and Yan-ni Chen}, title={Study on the Dynamics of Virus Propagation in Combination with Big Data and Kinetic Models}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Viral transmission Big data Kinetic model Differential equation}, doi={10.1007/978-3-030-67874-6_4} }- Guo-bin Zeng
Yan-ni Chen
Year: 2021
Study on the Dynamics of Virus Propagation in Combination with Big Data and Kinetic Models
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_4
Abstract
With the continuous development of science and technology, in the context of current big data, the research on the law of traditional virus propagation dynamics had been developed to the bottleneck. The traditional law of virus propagation dynamics was less sensitive and the mathematical model was not easy to operate. Therefore, it was proposed to study the dynamics of viral propagation based on the combination of big data and kinetic models. The model was established by using differential equations and so on, and the accurate prediction law of virus propagation dynamics was completed by experimental tracking control. A graph of the number of patients over time was obtained by bringing the problem into the model, and the changes in the model results were derived from this graph. In this way, corresponding countermeasures was drawn based on the changes in the results. Finally, through simulation experiments, it was proved that the combination of big data and kinetic model of viral propagation kinetics scientifically and accurately studied the laws of viral propagation dynamics. The established mathematical model was easy to operate and had a good guiding significance for practice.
