Data Driven Modelling of Coronavirus Spread in Spain

作     者：G.N.Baltas F.A.Prieto M.Frantzi C.R.Garcia-Alonso P.Rodriguez 

作者机构：Loyola Institute of Science and TechnologyUniversidad Loyola AndalucíaSeville41704Spain Department of Biomarker ResearchMosaiques Diagnostics GmbHHannover30659Germany Renewable Electrical Energy SystemsTechnical University of CataloniaTerrassa08222Spain 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2020年第64卷第9期

页      面：1343-1357页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work was supported by the European Commission under project FLEXITRANSTORE-H2020-LCE-2016-2017-SGS-774407 by the Spanish Ministry of Science under project ENE2017-88889-C2-1-R Any opinions,findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the host institutions or funders 

主　　题：Coronavirus deep neural network machine learning Monte Carlo simulation SIR model 

摘      要：During the late months of last year,a novel coronavirus was detected in Hubei,*** virus,since then,has spread all across the globe forcing Word Health Organization(WHO)to declare COVID-19 outbreak a *** Spain,the virus started infecting the country slowly until rapid growth of infected people occurred in Madrid,Barcelona and other major *** government in an attempt to stop the rapssid spread of the virus and ensure that health system will not reach its capacity,implement strict measures by putting the entire country in *** duration of these measures,depends on the evolution of the virus in *** this study,a Deep Neural Network approach using Monte Carlo is proposed for generating a database to train networks for estimating the optimal parameters of a SIR epidemiology *** number of total infected people as of April 7 in Spain is considered as input to the Deep Neural *** adaptability of the model was evaluated using the latest data upon completion of this paper,i.e.,April *** date range for the peak of infected people(i.e.,active cases)based on the new information is estimated to be within 74 to 109 days after the first recorded case of COVID-19 in *** addition,a curve fitting measure based on the squared Euclidean distance indicates that according to the current data the peak might occur before the 86th ***,Deep Neural Networks have proven accurate and useful tools in handling big epidemiological data and for peak prediction estimates.