"In 2009, the Naval Oceanographic Office was tasked with developing a product that uses forecasted meteorological conditions and historical pirate incidents to predict locations conducive to pirate activity in the Somali Basin Region and the Gulf of Aden. This resulted in the development of the Piracy Performance Surface (PPS) model, whose outputs are briefed daily to the Commander 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."
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