论文标题
机器学习的应用预测COVID-19的传播
Application of machine learning for predicting the spread of COVID-19
论文作者
论文摘要
多年来已经研究了疾病的传播，但是由于COVID-19的爆发和传播，最近它已获得特别的重点。研究表明，COVID-19的传播可以以易感性感染的已经遗产（SIRD）模型（由于隔离并保持社交距离）为特征。该项目旨在应用机器学习技术来预测Covid-19的严重性以及隔离的影响，保持社交距离，在家工作以及戴口罩对疾病的传播。这项工作加深了我们对疾病传播的理解，并揭示了以下政策的重要性。
The spread of diseases has been studied for many years, but it receives a particular focus recently due to the outbreak and spread of COVID-19. Studies show that the spread of COVID-19 can be characterized by the Susceptible-Infectious-Recovered-Deceased (SIRD) model with containment coefficients (due to quarantine and keeping social distance). This project aims to apply the machine learning technique to predict the severity of COVID-19 and the effect of quarantine, keeping social distance, working from home, and wearing masks on the transmission of the disease. This work deepens our understanding of disease transmission and reveals the importance of following policies.
