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dc.contributor.authorBurns, Meghan Colleenen_US
dc.date.accessioned2018-05-24T08:00:17Z
dc.date.available2018-05-24T08:00:17Z
dc.date.issued2018-05-23en_US
dc.identifier.othervt_gsexam:15170en_US
dc.identifier.urihttp://hdl.handle.net/10919/83381
dc.description.abstractThis thesis compares three variations of the Bayesian network as an aid for decision-making using uncertain information. After reviewing the basic theory underlying probabilistic graphical models and Bayesian estimation, the thesis presents a user-defined static Bayesian network, a static Bayesian network in which the parameter values are learned from data, and a dynamic Bayesian network with learning. As a basis for the comparison, these models are used to provide a prior assessment of the safety of flight of a small unmanned aircraft, taking into consideration the state of the aircraft and weather. The results of the analysis indicate that the dynamic Bayesian network is more effective than the static networks at predicting safety of flight.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis item is protected by copyright and/or related rights. Some uses of this item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectDynamic Bayesian Networken_US
dc.subjectUnmanned Aerial Systemsen_US
dc.subjectRisken_US
dc.titleSafety of Flight Prediction for Small Unmanned Aerial Vehicles Using Dynamic Bayesian Networksen_US
dc.typeThesisen_US
dc.contributor.departmentAerospace and Ocean Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineAerospace Engineeringen_US
dc.contributor.committeechairWoolsey, Craig A.en_US
dc.contributor.committeememberPatil, Mayuresh J.en_US
dc.contributor.committeememberAdams, Richard E.en_US


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