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A model for geographically distributed combat interactions of swarming naval and air forces 下载免费PDF全文
This article describes the Distributed Interaction Campaign Model (DICM), an exploratory campaign analysis tool and asset allocation decision‐aid for managing geographically distributed and swarming naval and air forces. The model is capable of fast operation, while accounting for uncertainty in an opponent's plan. It is intended for use by commanders and analysts who have limited time for model runs, or a finite budget. The model is purpose‐built for the Pentagon's Office of Net Assessment, and supports analysis of the following questions: What happens when swarms of geographically distributed naval and air forces engage each other and what are the key elements of the opponents’ force to attack? Are there changes to force structure that make a force more effective, and what impacts will disruptions in enemy command and control and wide‐area surveillance have? Which insights are to be gained by fast exploratory mathematical/computational campaign analysis to augment and replace expensive and time‐consuming simulations? An illustrative example of model use is described in a simple test scenario. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 562–576, 2016 相似文献
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在分析作战仿真对战场环境信息需求的基础上,得出自主制作矢量图是满足此类需求的最理想方法。在此基础上设计了一种具有操作开放功能的矢量图数据结构。该结构秉承面向对象的设计思想,提供了丰富的使用接口,为矢量图及其数据的编辑、操作、交互使用和二次开发等实际应用提供了便利。实验证明以该数据结构组织数据的矢量图具有良好的可操作性和可拓展性。 相似文献
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装备的损坏率是决定装备维修保障的重要依据,通过对装备战损率及其分布的分析,给出了在维修机构修复能力一定的条件下相应的损坏率及其分布的模型,可为装备维修保障提供决策。 相似文献
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基于区间数TOPSIS法优选空军战役作战计划 总被引:1,自引:0,他引:1
针对战役作战计划优选中的不确定性,运用区间分析和TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)法探索空军战役作战计划优选问题.通过引进区间数乘法运算,将区间数多指标决策问题转变为指标为区间数的多指标决策问题,进而给出区间数多指标决策问题的TOPSIS法,对空军战役作战计划进行排序选优.与传统方法相比较,该方法较好地解决了评价指标为不确定值时的多指标决策问题. 相似文献
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The article develops a theorem which shows that the Lanchester linear war equations are not in general equal to the Kolmogorov linear war equations. The latter are time‐consuming to solve, and speed is important when a large number of simulations must be run to examine a large parameter space. Run times are provided, where time is a scarce factor in warfare. Four time efficient approximations are presented in the form of ordinary differential equations for the expected sizes and variances of each group, and the covariance, accounting for reinforcement and withdrawal of forces. The approximations are compared with “exact” Monte Carlo simulations and empirics from the WWII Ardennes campaign. The band spanned out by plus versus minus the incremented standard deviations captures some of the scatter in the empirics, but not all. With stochastically varying combat effectiveness coefficients, a substantial part of the scatter in the empirics is contained. The model is used to forecast possible futures. The implications of increasing the combat effectiveness coefficient governing the size of the Allied force, and injecting reinforcement to the German force during the Campaign, are evaluated, with variance assessments. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005. 相似文献
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战役情报是组织实施战役所需的军事情报,运用模糊层次分析法对战役情报的效能进行评估,可以对军队情报工作产生一定程度的导向作用,进而促使增强情报工作的针对性,优化情报工作流程和资源配置。模糊层次分析法具有较高的科学性和客观性,计算方法简单、使用方便,通过应用实例表明模糊层次分析法对于衡量某特定情报集在战役中的支持力度具有一定的参考价值。 相似文献
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