发帖
雷达卡
摘要翻译：
我们引入了经典隔间SIR（易感、感染、康复）流行病模型的数字孪生，并研究了数字孪生与系统之间的相互关系。在这样做时，我们使用Stieltjes导数将数据从真实系统提供给虚拟模型，作为回报，虚拟模型实时地改进了它。作为模型的副产品，我们给出了问题解的精确数学定义。我们还分析了解的存在唯一性，引入了主数字孪生的概念，并用新冠肺炎疫情的实际数据进行了数值模拟，表明了所提思想的准确性。
---
英文标题：
《A Digital Twin of a Compartmental Epidemiological Model based on a
Stieltjes Differential Equation》
---
作者：
Iv\'an Area, F.J. Fern\'andez, Juan J. Nieto, F. Adri\'an F. Tojo
---
最新提交年份：
2021
---
分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
--
---
英文摘要：
We introduce a digital twin of the classical compartmental SIR (Susceptible, Infected, Recovered) epidemic model and study the interrelation between the digital twin and the system. In doing so, we use Stieltjes derivatives to feed the data from the real system to the virtual model which, in return, improves it in real time. As a byproduct of the model, we present a precise mathematical definition of solution to the problem. We also analyze the existence and uniqueness of solutions, introduce the concept of Main Digital Twin and present some numerical simulations with real data of the COVID-19 epidemic, showing the accuracy of the proposed ideas.
---
PDF链接：
https://arxiv.org/pdf/2105.02217
京公网安备 11010802022788号
