摘要: |
目的:应用风险分析的理论方法改进现行预测方法。方法:以城市进攻作战减员预计为例,整理分析了历史数据和影响减员的不确定因素,确定了日均减员率的统计分布,以定量判断模型为基础,设定参战人数、地形、气候、态势、突然性、战斗效能等因素,应用蒙特卡罗方法进行模拟,采用Microsoft Excel和Crystal Ball 2000建立了相应的预测模型,对减员模拟结果进行风险分析。结果:城市进攻作战日均减员率可用正态分布变量表达。结合上述因素的量化值,1 000模拟的结果为,日均战斗减员率均数0.42%,标准差0.21%。结论:蒙特卡罗模拟方法是改进现行预测方法的有效手段。 |
关键词: 蒙特卡罗法 减员预计 风险分析 |
DOI:10.3724/SP.J.1008.2008.00826 |
投稿时间:2007-12-19修订日期:2008-05-19 |
基金项目:第二军医大学青年启动基金(2003SQ17). |
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Monte Carlo Simulation in risk analysis of battle casualty forecasting in urban aggressive military action |
DENG Yue-xian1,QIN Chao1*,LI Rui-xing2,PENG Hai-wen1,JIANG Lei1 |
(1.Department of Military Health Service,Faculty of Health Services,Second Military Medical University,Shanghai 200433,China;2.Division of Comprehensive Administration,Medical Department,General Logistics Department of PLA,Beijing 100842) |
Abstract: |
Objective:To improve the present method for casualty forecasting using the risk analysis theory.Methods: Empirical data were extracted from 11 urban aggressive combats during and after WW Ⅱ,and the distribution of daily casualty was determined.Based on quantitative judgment model,several factors such as the number of soldiers,terrain,weather,general situation,suddenness, and combat efficacy were configured; Monte Carlo simulation was applied for simulation,and a forecasting model was setup with Microsoft Excel and Crystal Ball 2000 software for risk analysis of the simulation outcome.Results: The distribution of daily casualty during urban aggressive military action could be represented by normal distribution.With the values of the aforementioned factors,the result of 1000 tests showed that the mean daily casualty rate was 0.42%,with the standard deviation being 0.21%.Conclusion: Monte Carlo simulation is an effective means to improve the present casualty forecasting method. |
Key words: monte carlo method casualty forecasting risk analysis |