Fitting Lanchester Equations to the Battles of Kursk and Ardennes
Abstract
Lanchester equations and their extensions are widely used to calculate attrition in
models of warfare. This paper examines how Lanchester models fit detailed daily data on the
battles of Kursk and Ardennes. The data on Kursk, often called the greatest tank battle in history,
was only recently made available. A new approach is used to find the optimal parameter values
and gain an understanding of how well various parameter combinations explain the battles. It
turns out that a variety of Lanchester models fit the data about as well. This explains why
previous studies on Ardennes, using different minimization techniques and data formulations,
have found disparate optimal fits. We also find that none of the basic Lanchester laws (i.e.,
square, linear, and logarithmic) fit the data particularly well or consistently perform better than
the others. This means that it does not matter which of these laws you use, for with the right
coefficients you will get about the same result. Furthermore, no constant attrition coefficient
Lanchester law fits very well. The failure to find a good-fitting Lanchester model suggests that
it may be beneficial to look for new ways to model highly aggregated attrition.
Description
The article of record as published may be found at http://dx.doi.org/10.1002/nav.10101
Rights
This 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.Collections
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