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dc.contributor.authorCihan, Pınar
dc.date.accessioned2023-04-20T08:04:13Z
dc.date.available2023-04-20T08:04:13Z
dc.date.issued2021
dc.identifier.isbn978-1-6654-3649-6
dc.identifier.urihttps://doi.org/10.1109/SIU53274.2021.9477773
dc.identifier.urihttps://hdl.handle.net/20.500.11776/11018
dc.description29th IEEE Conference on Signal Processing and Communications Applications (SIU) -- JUN 09-11, 2021 -- ELECTR NETWORKen_US
dc.description.abstractThe coronavirus pandemic first started in Wuhan, China. The pandemic then spread rapidly all over the world. The virus wreaked unprecedented havoc worldwide. Researchers are using a variety of mathematical and machine learning-based prediction models to predict the future trend of the pandemic. In this study, autoregressive integrated moving average (ARIMA) models were developed to forecast the expected daily confirmed COVID-19 cases for the next two weeks in the United States (USA) and India, which are most affected by the pandemic. ARIMA (0,2,1) and ARIMA (1,2,3) models with the lowest mean absolute percent error (MAPE) were selected as the best models for USA and India, respectively (MAPE(US)(A)=1.04%, MAPE(INDIA)=0.41%). According to these models, it is predicted that the total number of cases in the USA will be 27.201 million and 10.788 million in India on February 04, 2021. This study shows that ARIMA models are suitable for predicting the prevalence of COVID-19 in the future. Analysis results can shed light on understanding the trends of the pandemic in these countries.en_US
dc.description.sponsorshipIEEE,IEEE Turkey Secten_US
dc.language.isoturen_US
dc.publisherIEEEen_US
dc.identifier.doi10.1109/SIU53274.2021.9477773
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCovid-19en_US
dc.subjectPandemicen_US
dc.subjectForecastingen_US
dc.subjectArimaen_US
dc.subjectUsaen_US
dc.subjectIndiaen_US
dc.titleARIMA-Based Forecasting of Total COVID-19 Cases in the USA and Indiaen_US
dc.typeconferenceObjecten_US
dc.relation.ispartof29th Ieee Conference On Signal Processing and Communications Applications (Siu 2021)en_US
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.institutionauthorCihan, Pınar
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.wosWOS:000808100700017en_US
dc.identifier.scopus2-s2.0-85111463230en_US


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