论文标题
建模和预测希腊中的共vid-19颞时间扩散：基于复杂网络定义的花样的探索方法
Modeling and forecasting the COVID-19 temporal spread in Greece: an exploratory approach based on complex network defined splines
论文作者
论文摘要
在抗COVID-19卫生管理的复杂框架内，诊断测试的标准，公共卫生资源和服务的可用性以及国家之间所应用的抗COVID-19策略在国家之间有所不同，在全球范围内，在全球范围内对临时差异的建模可靠性和准确性可以证明是有效的。本文将探索性的时间序列分析应用于希腊疾病的演变，目前暗示了Covid-19 Management的成功故事。所提出的方法建立在时间序列中检测结缔组织的最新概念上，并开发出一种新型的样条回归模型，在该模型中，结的结构是由复杂网络中的社区检测确定的。总体而言，这项研究通过提出没有断开的过去数据和可靠的预测框架来促进Covid-19的研究，这可以促进对可用健康资源的决策和管理。
Within the complex framework of anti-COVID-19 health management, where the criteria of diagnostic testing, the availability of public-health resources and services, and the applied anti-COVID-19 policies vary between countries, the reliability and the accuracy in the modeling of temporal spread can be proven effective in the worldwide fight against the disease. This paper applies an exploratory time-series analysis to the evolution of the disease in Greece, which currently suggests a success story of COVID-19 management. The proposed method builds on a recent conceptualization of detecting connective communities in a time-series and develops a novel spline regression model where the knot vector is determined by the community detection in the complex network. Overall, the study contributes to the COVID-19 research by proposing a free of disconnected past-data and reliable framework of forecasting, which can facilitate decision-making and management of the available health resources.
