Neural network aided aviation fuel consumption modeling

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dc.contributor.authorCheung, Wing Hoen
dc.contributor.committeechairTrani, Antoino A.en
dc.contributor.committeememberDrew, David R.en
dc.contributor.committeememberGreene, Richard G.en
dc.contributor.departmentCivil Engineeringen
dc.date.accessioned2014-03-14T20:52:26Zen
dc.date.adate1997-10-01en
dc.date.available2014-03-14T20:52:26Zen
dc.date.issued1997-08-25en
dc.date.rdate1997-10-01en
dc.date.sdate1997-08-25en
dc.description.abstractThis thesis deals with the potential application of neural network technology to aviation fuel consumption estimation. This is achieved by developing neural networks representative jet aircraft. Fuel consumption information obtained directly from the pilot's flight manual was trained by the neural network. The trained network was able to accurately and efficiently estimate fuel consumption of an aircraft for a given mission. Statistical analysis was conducted to test the reliability of this model for all segments of flight. Since the neural network model does not require any wind tunnel testing nor extensive aircraft analysis, compared to existing models used in aviation simulation programs, this model shows good potential. The design of the model is described in depth, and the MATLAB source code are included in appendices.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-82597-205125en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-82597-205125/en
dc.identifier.urihttp://hdl.handle.net/10919/36998en
dc.publisherVirginia Techen
dc.relation.haspartThesis.PDFen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectneural networken
dc.subjectfuel consumptionen
dc.subjectaviationen
dc.titleNeural network aided aviation fuel consumption modelingen
dc.typeThesisen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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