Monte Carlo方法在计算机辅助布防中的应用

借助于统计推断的有关原理,提出了一种评估多个火力单元射击一批目标教果的方法。该方法可以为防空批导武器系统的合理布置提供参考,也可以用于评估一个已布置的防空反导系统的有效防卫能力,为最大限度地利用防空反导兵器提供依据。     

毫米波相控阵雷达弹丸脱靶量检测概率分析

定量分析了雷达检测波门及波位的设置、搜索周期、目标及弹丸运动的速度,方向等因素对弹丸检测概率的影响,并针对给定的参数和航路对检测概率进行了计算机仿真。     

应用Bayes分析方法鉴定误码率

本文应用了Bayes分析方法,即依据样本考虑先验知识,进行统计推断“可信度”。由此推导出了误码率计算公式,从而在数据传输试验中实现了不需要测试设备,只需计算重发次数,传输总次数,即可求得误码率,同时给出其风险,为科学鉴定误码率提供了理论依据。     

带紧扰动的集值(S)_+型映射的拓扑度及其应用

本文利用 Michael 连续选择定理与 F.E Browder 次连续(S)_+型映射度理论相结合的方法,构造了带紧扰动的1.s.c.集值(S)_+型映射的拓扑度,并讨论了作为其应用的不动点与值域问题.     

模拟法计算自导鱼雷命中概率的检测模型

系统、深入地阐述了检测模型的建立与使用等问题,并讨论了如何通过检测模型的有关处理,考虑鱼雷实航工作中各种因素的影响。最后以ＭＫ４６鱼雷为例,讨论了检测逻辑判别问题     

关联维数在转子系统状态监测应用时参数选择的实验研究

给出了转子系统状态的关联维数方法,通过获取大量实验数据来计算关联维数。在此基础上讨论了在计算关联维数时如何选择合适的重构相空间的矢量数、嵌入维数、时间延迟及矢量间间距等参数,最后给出了分析结果。     

仓库机械设备的综合评价模型

建立了综合评价仓库机械性能的指标体系,根据这一指标体系提出模糊综合评价和成本分析的方法,应用这些方法对我军仓库目前使用的几种机械作了评价,找出了费效比最大的机械。     

Combined variance reduction techniques in fully sequential selection procedures

In the past several decades, many ranking‐and‐selection (R&S) procedures have been developed to select the best simulated system with the largest (or smallest) mean performance measure from a finite number of alternatives. A major issue to address in these R&S problems is to balance the trade‐off between the effectiveness (ie, making a correct selection with a high probability) and the efficiency (ie, using a small total number of observations). In this paper, we take a frequentist's point of view by setting a predetermined probability of correct selection while trying to reduce the total sample size, that is, to improve the efficiency but also maintain the effectiveness. In particular, in order to achieve this goal, we investigate combining various variance reduction techniques into the fully sequential framework, resulting in different R&S procedures with either finite‐time or asymptotic statistical validity. Extensive numerical experiments show great improvement in the efficiency of our proposed procedures as compared with several existing procedures.     

Augmented nested sampling for stochastic programs with recourse and endogenous uncertainty

We propose a novel simulation‐based approach for solving two‐stage stochastic programs with recourse and endogenous (decision dependent) uncertainty. The proposed augmented nested sampling approach recasts the stochastic optimization problem as a simulation problem by treating the decision variables as random. The optimal decision is obtained via the mode of the augmented probability model. We illustrate our methodology on a newsvendor problem with stock‐dependent uncertain demand both in single and multi‐item (news‐stand) cases. We provide performance comparisons with Markov chain Monte Carlo and traditional Monte Carlo simulation‐based optimization schemes. Finally, we conclude with directions for future research.     

基于正交设计的反舰导弹末制导雷达参数优化

分析了反舰导弹末制导雷达的目标捕捉的限制条件,以一种典型的目标态势为前提建立了基于蒙特卡洛仿真法的目标捕捉概率计算模型,在此基础上利用正交设计的方法对末制导雷达参数组合进行寻优,并通过调整重要因素水平进行多次实验,得到了适合当前目标态势的较优参数组合,为提高反舰导弹目标捕捉能力的相关研究提供了参考。