Flight Data to Predict COVID-19 Cases by Machine Learning

dc.contributor.author	Alshabana, Ghadah
dc.date.accessioned	2022-01-20T00:12:05Z
dc.date.available	2022-01-20T00:12:05Z
dc.date.issued	2021-04-28
dc.identifier.uri	http://hdl.handle.net/1920/12223
dc.description.abstract	Coronavirus 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.	en_US
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	COVID-19	en_US
dc.subject	machine learning	en_US
dc.title	Flight Data to Predict COVID-19 Cases by Machine Learning	en_US
dc.type	Working Paper	en_US