文章基本信息

标题：Modeling of Coronavirus Behavior to Predict it’s Spread
本地全文：下载
作者：Shakir Khan ; Amani Alfaifi
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2020
卷号：11
期号：5
DOI：10.14569/IJACSA.2020.0110552
出版社：Science and Information Society (SAI)
摘要：With the increasing presence and feast of infectious diseases and their fatalities in densest areas, many academics and societies have become fascinated in discovering new behaviors to predict these diseases' feast behaviors. This media will help them to plan and contain the disease better in trivial provinces and thus decrease the beating of human lives. Some cases of an indeterminate cause of pneumonia occurred in Wuhan, Hubei, China, in December 2019, with clinical presentations closely resembling viral pneumonia. In-depth analyzes of the sequencing from lower respiratory tract samples discovered a novel coronavirus, called 2019 novel coronavirus (2019-nCoV). Current events showed us how easily a coronavirus could take root and spread—such viruses transmitted easily between persons. To cure with these infections, we applied time series forecasting model in this paper to predict possible coronavirus events. The forecasting model applied is SIR. The results of the implemented models compared with the actual data.
关键词：COVID-19; coronavirus; SIR model; data mining; R Software; forecasting model