Borah Manash Jyoti, Hazarika Bipan, Panda Sumati Kumari, Nieto Juan Jose
Department of Mathematics, Bahona College, Jorhat 785 101, Assam, India.
Department of Mathematics, Gauhati University, Guwahati 781 014, Assam, India.
Results Phys. 2020 Dec;19:103587. doi: 10.1016/j.rinp.2020.103587. Epub 2020 Nov 18.
In this article, for the analysis of Covid-19 progression in India, we present new insights to formulate a data-driven epidemic model and approximation algorithm using the real data on infection, recovery and death cases with respect to weather in the view of mathematical variables.
在本文中,为了分析印度新冠肺炎的发展情况,我们从数学变量的角度出发,利用感染、康复和死亡病例的实际数据以及天气数据,提出了新的见解,以构建一个数据驱动的疫情模型和近似算法。