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Predicting Global Disposition Of U.S. Military Personnel Via Open-Source, Unclassified Means.
| 题名： | Predicting Global Disposition Of U.S. Military Personnel Via Open-Source, Unclassified Means. |
| 作者： | Small, M. T. |
| 关键词： | Time series analysis, Smoothing (mathematics), Errors, Regression analysis, Military personnel, Mathematical models, Personnel management, United states transportation command, Exponential smoothing, Arima, Regression with arima errors |
| 摘要： | Demand of USTRANSCOM assets are subject to fluctuations due to unforeseen circumstances such as war, conflict, natural disasters, and other calamities requiring the presence of military personnel. This study evaluates the use of forecasting models to predict the number of military personnel expected by branch and country each year. The expectation by USTRANSCOM is that accurate forecasts for the number of military personnel in each country can be leveraged to develop alternative transportation workload forecasts of demand of USTRANSCOM assets. There was not a single model that performed best for all countries and branches of service. Each model was analyzed via the traditional 80/20 forecasting evaluation metric as well as a two-year horizon cross-validation metric. The exponential smoothing model with a high level of performed quite well for many of the models, indicating that perhaps simpler models will still provide accurate forecasts. Further research is needed to determine whether incorporating forecasts of military personnel will improve the ability to forecast demand of USTRANSCOM assets. |
| 报告类型： | 科技报告 |
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