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dc.contributor.authorLucas, Thomas W.
dc.contributor.authorSanchez, Susan M.
dc.datePeriod of Perforance: 12/1/14 - 12/31/15
dc.date.accessioned2018-04-19T01:48:54Z
dc.date.available2018-04-19T01:48:54Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/10945/57943
dc.descriptionProfessor Thomas W. Lucas and Professor Susan M. Sanchez
dc.description.abstractThe objective of this research was to improve upon the ability of OPNAV N1 analysts to quickly and efficiently obtain experimental information from their computational models. This will allow N1 to quickly identify and quantify the potential impacts of numerous resource and policy options. To accomplish this goal, the research assessed the feasibility and potential benefits of data farming with a selected manpower modelラthat is, embedding the chosen N1 manpower, personnel, training, and education (MPTE) tool in an environment that enables efficiently running and analyzing designed experiments over a breadth of input variables, thereby creating model-driven big data. The chosen model was the Officer Strategic Analysis Model (OSAM), and we also made some initial explorations of the Navy Total Force Strength Model (NTFSM).en_US
dc.description.sponsorshipNaval Research Programen_US
dc.description.sponsorshipPrepared for: OPNAV N1 N1Z, Mr. Ilia Christman, Mr. Wayne Wagner, LCDR William Corley, and Mr. Ian Andersonen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleImproving Navy MPTE Studies with Model-Driven Big Dataen_US
dc.typeReporten_US
dc.contributor.corporateNaval Postgraduate School
dc.contributor.corporateNaval Research Program


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