• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.56-69
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• 2002

A technique of finding both probability density and distribution function for interkilling times is considered and demonstrated. An important result is that any arbitrary interfiring time random variables fit to this study, The interfiring renewal density function given a certain interfiring probability density function can be applied to obtain the corresponding interkilling renewal density function which helps us to estimate the expected number of killing events in a time period. The numerical inversion of Laplace transformation makes these possible and the results appear to be excellent. In case of ammunition supply is limited, an alternative way of getting the probability density function of time to the killing is investigated. The convolution technique may give us a means of settling for this new problem.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.974-974
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• 1995

• Journal of the military operations research society of Korea
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• v.29 no.2
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• pp.1-12
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• 2003

Knowing the characteristic of battle duration is important for commanders and logicians in the analysis of combat realization. Analytic solutions for mean and standard deviation can be found in small sized battles. Stochastic combat simulation model is utilized to study a probabilistic behavior of the combat duration. Output data is fitted to a certain probability distribution and some moments such as skewness and kurtosis are investigated. Fire allocation strategies, reselect options, interfiring time random variables, and kill rates are considered to investigate how they affect the battle termination time.

• Journal of the Korea Society for Simulation
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• v.18 no.1
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• pp.53-62
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• 2009

The real data obtained from field exercises has a crucial role in modeling and simulation of a combat or a wargame. This becomes an important input especially in analyzing weapon systems realization. Many existing models have been using the mean value of the time between each fire. The firing data can be incorporated into a known probability distribution or used directly as an empirical distribution. Data of field exercises are very useful instead of the real combat outcomes. This study finds a new modeling approach and techniques to compare the data with the previously generated outcomes. This fundamental research work will continue to consider more of the various weapon systems, the sizes, and other tactical aspects.