论文标题
全国性衡量标准的影响研究COVID-19反流行：隔室模型和机器学习
Impact studies of nationwide measures COVID-19 anti-pandemic: compartmental model and machine learning
论文作者
论文摘要
在本文中，我们研究了全国性衡量措施Covid-19反流行病的影响。我们驱动两个过程来分析COVID-19考虑措施的数据。我们将全国范围的度量与与模型的接触率有关的参数值联系起来。然后，就那些度量参数而言，参数求解显示了大流行进化的不同可能性。两个机器学习工具用于预测大流行的演变。最后，我们展示了确定性和两个机器学习工具之间的比较。
In this paper, we deal with the study of the impact of nationwide measures COVID-19 anti-pandemic. We drive two processes to analyze COVID-19 data considering measures. We associate level of nationwide measure with value of parameters related to the contact rate of the model. Then a parametric solve, with respect to those parameters of measures, shows different possibilities of the evolution of the pandemic. Two machine learning tools are used to forecast the evolution of the pandemic. Finally, we show comparison between deterministic and two machine learning tools.
