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dc.contributor.advisorLucas, Thomas W.
dc.contributor.advisorSingham, Dashi I.
dc.contributor.authorSeymour, Christian N.
dc.dateSep-14
dc.date.accessioned2014-12-05T20:10:52Z
dc.date.available2014-12-05T20:10:52Z
dc.date.issued2014-09
dc.identifier.urihttps://hdl.handle.net/10945/44000
dc.description.abstractThe Synthetic Theater Operations Research Model (STORM) is the primary campaign analysis tool used by the Office of the Chief of Naval Operations, Assessment Division (OPNAV N81) and other Department of Defense organizations to aid in providing analysis to top-level officials on force structures, operational concepts, and military capabilities. This thesis describes how STORM works, analyzes the variability associated with many replications, and evaluates the trade-off between the expected number of replications and the precision and probability of coverage of confidence intervals. The results of this research provide OPNAV 81 with the ability to capitalize on STORM’s full potential on a time-line conducive to its high-paced environment. The distribution of outcomes is examined via standard statistical techniques for multiple metrics. All metrics appear to have sufficient variability, which is critical in modeling the combat environment. The trade-off for confidence intervals between the expected number of replications, precision, and the probability of coverage is very important. If a more precise solution and a higher probability of coverage are required, more replications are generally needed. This relationship is explored and a framework is provided to conduct this analysis on simulation output data.en_US
dc.description.urihttp://archive.org/details/capturingfullpot1094544000
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.titleCapturing the full potential of the Synthetic Theater Operations Research Model (STORM)en_US
dc.typeThesisen_US
dc.contributor.secondreaderSilvestrini, Rachel
dc.contributor.departmentOperations Research
dc.subject.authorSynthetic Theater Operations Research Model (STORM)en_US
dc.subject.authorN81en_US
dc.subject.authorcampaign-level simulationen_US
dc.subject.authorstopping rulesen_US
dc.subject.authorconfidence interval proceduresen_US
dc.subject.authorStormMineren_US
dc.subject.authorsimulationen_US
dc.description.recognitionOutstanding Thesisen_US
dc.description.serviceLieutenant, United States Navyen_US
etd.thesisdegree.nameMaster of Science in Operations Researchen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineOperations Researchen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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