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        A further comparison of deterministic and stochastic Lanchester-type combat models

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        Iconfurthercompariso00klem.pdf (3.996Mb)
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        Author
        Klemm, Kurt Dieter
        Date
        1980-09
        Advisor
        Taylor, James T.
        Second Reader
        Lindsay, George F.
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        Abstract
        This thesis examines the differences of deterministic and stochastic LANCHESTER-type combat models. Using an example of square-law attrition, solution methods and solutions are described. A new analytic solution for equal attrition rate coefficients is given. The numerical comparison includes hypothesis about the expected force levels and the variability in the expected force levels as a function of time, initial force levels, and breakpoint force levels.
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        Approved for public release, distribution is unlimited.
        URI
        http://hdl.handle.net/10945/18967
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        • 1. Thesis and Dissertation Collection, all items

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          The effect of uncertainty on Lanchester type equations of combat 

          Craig, James David (Monterey, California. Naval Postgraduate School, 1975-09);
          This thesis examines whether the complex random process of combat can be adequately represented by a deterministic model. Does one destroy any of the essential features of the random combat process by considering a ...
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          Application of differential games to problems of military conflict: Tactical allocation problems, Part II 

          Taylor, James G. (Monterey, California. Naval Postgraduate School, 1972-11); NPS55TW72111A
          The mathematical theory of optimal control/differential games is used to study the structure of optimal allocation policies for some tactical allocation problems with combat described by Lanchester-type equations of warfare. ...
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          Incorporating ensemble-based probabilistic forecasts into a campaign simulation in the Weather Impact Assessment Tool (WIAT) 

          Palmer, Jeffrey M. (Monterey, California. Naval Postgraduate School, 2010-06);
          Stochastic (probabilistic) forecasting techniques give forecasters a means to transmit information about certainty and a range of forecast possibilities to operational decision makers. Previous studies have shown value in ...
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