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dc.contributor.advisorHasenbein, John J.en
dc.creatorTondukulam Seeth, Srikanthen
dc.date.accessioned2011-02-21T21:12:34Zen
dc.date.accessioned2011-02-21T21:12:52Zen
dc.date.available2011-02-21T21:12:34Zen
dc.date.available2011-02-21T21:12:52Zen
dc.date.issued2010-12en
dc.date.submittedDecember 2010en
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2010-12-2259en
dc.descriptiontexten
dc.description.abstractThis report examines the trends in sick leave usage among nurses in a hospital and aims at creating a forecasting model to predict sick leave usage on a weekly basis using the concept of artificial neural networks (ANN). The data used for the research includes the absenteeism (sick leave) reports for 3 years at a hospital. The analysis shows that there are certain factors that lead to a rise or fall in the weekly sick leave usage. The ANN model tries to capture the effect of these factors and forecasts the sick leave usage for a 1 year horizon based on what it has learned from the behavior of the historical data from the previous 2 years. The various parameters of the model are determined and the model is constructed and tested for its forecasting ability.en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.subjectArtificial neural networksen
dc.subjectForecastingen
dc.subjectNursingen
dc.subjectNursesen
dc.subjectAbsenteeismen
dc.titleForecasting of sick leave usage among nurses via artificial neural networksen
dc.date.updated2011-02-21T21:12:53Zen
dc.contributor.committeeMemberPopova, Elmiraen
dc.description.departmentOperations Research and Industrial Engineeringen
dc.type.genrethesisen
thesis.degree.departmentOperations Research and Industrial Engineeringen
thesis.degree.disciplineOperations Research and Industrial Engineeringen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Engineeringen


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