Sidharth Saxena, R. Shettar
{"title":"Forecasting the coronavirus disease 2019 pandemic in India using machine learning and statistical models","authors":"Sidharth Saxena, R. Shettar","doi":"10.1504/ijmmno.2022.10046707","DOIUrl":null,"url":null,"abstract":"COVID-19, which is an infectious disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has resulted in a massive blow to India with respect to the health of its citizens and economy. The work in this paper focuses on the Prophet model, linear regression model, Holt's model and the ARIMA model for predicting the number of confirmed, recovered cases, deaths and active cases along with growth rate, recovery rate and mortality rate in India for the month of November 2020. The performance of all the above mentioned models has been evaluated using standard metrics namely R2, adjusted R2, root-mean-square error and mean absolute error. © 2022 Inderscience Enterprises Ltd.","PeriodicalId":13553,"journal":{"name":"Int. J. Math. Model. Numer. Optimisation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Math. Model. Numer. Optimisation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijmmno.2022.10046707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
利用机器学习和统计模型预测2019年印度冠状病毒大流行
COVID-19是由严重急性呼吸系统综合征冠状病毒-2 (SARS-CoV-2)引起的传染病,给印度公民的健康和经济造成了巨大打击。本文的工作重点是先知模型、线性回归模型、霍尔特模型和ARIMA模型,用于预测2020年11月印度的确诊病例、康复病例、死亡病例和活跃病例数量以及增长率、康复率和死亡率。采用标准指标R2、调整后R2、均方根误差和平均绝对误差对上述所有模型的性能进行了评价。©2022 Inderscience Enterprises Ltd
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