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dc.contributor.advisorRegnier, Eva
dc.contributor.advisorHansen, James A.
dc.contributor.authorSlootmaker, Leslie A.
dc.date.accessioned2012-03-14T17:46:36Z
dc.date.available2012-03-14T17:46:36Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/10945/5747
dc.description.abstracter of the United States Naval Forces Central Command and Combined Maritime Forces in Bahrain. The Next-generation PPS (PPSN) model uses simulation to provide as output, a forecast of relative pirate presence probability over time. Effective March 1, 2011, the name of PPSN has been changed to the Pirate Attack Risk Surface (PARS) model. This research includes interviews with counter-piracy forces that led to recommended changes in the PPSN model. In addition, using robust and realistic experimental designs, this research identifies the significant intelligence factors of the PPSN model. This gathered information is being used to refine these input variables to achieve maximum performance of the PPSN model. This research also unveiled input variables that are influential in the computing memory requirements and program runtime. This information is being used to focus efforts on setting these variables to realistic levels without sacrificing the model's efficiency and effectiveness. Finally, the results of this thesis allow for quick turnaround of updates to the PPSN model in response to gathered intelligence.en_US
dc.description.urihttp://archive.org/details/counteringpiracy109455747
dc.format.extentxxii, 77 p. : col. ill. (4 maps) ;en_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.subject.lcshPiracyen_US
dc.subject.lcshExperimental designen_US
dc.titleCountering piracy with the next generation piracy performance surface modelen_US
dc.typeThesisen_US
dc.contributor.secondreaderLucas, Thomas W.
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentOperations Research
dc.description.recognitionOutstanding Thesisen_US
dc.identifier.oclc720381923
etd.thesisdegree.nameM.S.en_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineOperations Researchen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
etd.verifiednoen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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