Flight Data to Predict COVID-19 Cases by Machine Learning

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dc.contributor.authorAlshabana, Ghadah
dc.date.accessioned2022-01-20T00:12:05Z
dc.date.available2022-01-20T00:12:05Z
dc.date.issued2021-04-28
dc.description.abstractCoronavirus can be transmitted through the air in close proximity to infected persons. Commercial aircraft is a likely way to both transmit the virus among passengers and move the virus between locations. Our team utilized machine learning to determine if the number of flights into the Washington DC Metro Area had an effect on the number of cases and deaths reported in the city and surrounding area.
dc.identifier.urihttps://hdl.handle.net/1920/12223
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.subjectCOVID-19
dc.subjectMachine learning
dc.titleFlight Data to Predict COVID-19 Cases by Machine Learning
dc.typeWorking Paper

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