期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Fighting against COVID-19: Who Failed and Who Succeeded?
1
作者 Hussein Baalbaki Hassan Harb +4 位作者 Ali Jaber Chamseddine Zaki Chady Abou Jaoude Kifah Tout Layla Tannoury 《Journal of Computer and Communications》 2022年第4期32-50,共19页
Recently, governments and public authorities in most countries had to face the outbreak of COVID-19 by adopting a set of policies. Consequently, some countries have succeeded in minimizing the number of confirmed case... Recently, governments and public authorities in most countries had to face the outbreak of COVID-19 by adopting a set of policies. Consequently, some countries have succeeded in minimizing the number of confirmed cases while the outbreak in other countries has led to their healthcare systems breakdown. In this work, we introduce an efficient framework called COMAP (COrona MAP), aiming to study and predict the behavior of COVID-19 based on deep learning techniques. COMAP consists of two stages: clustering and prediction. The first stage proposes a new algorithm called Co-means, allowing to group countries having similar behavior of COVID-19 into clusters. The second stage predicts the outbreak’s growth by introducing two adopted versions of LSTM and Prophet applied at country and continent scales. The simulations conducted on the data collected by WHO demonstrated the efficiency of COMAP in terms of returning accurate clustering and predictions. 展开更多
关键词 COVID-19 Data Clustering and Prediction co-means ANOVA LSTM PROPHET
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部