空域窗射击毁歼概率解析计算模型

为提高未来空域窗射击技术对空中机动目标的毁伤概率,需要根据目标机动幅度对未来空域窗的大小进行动态设定,故提出“自适应射击窗”的概念.空域窗大小设定的依据是使毁歼概率最优.可以采用解析法来在线计算该毁歼概率值.在分析空域窗射击误差的基础上,演绎了均匀分布法与高斯和法两种毁歼概率解析计算方法的公式.以毁歼概率蒙特卡罗法仿真数据为基准值,对两种解析法的计算精度进行了对比分析.仿真结果表明,高斯和法的计算精度显著优于均匀分布法,且满足实时计算要求,适于在线评估空域窗的射击效能.     

Dynamic regulation on innovation and adoption of green technology with information asymmetry

This study investigates a regulator's dynamic policy to motivate firms' research on and adoption of green technology. In the proposed model, a firm makes unobservable efforts and can hide the technology's arrival from the regulator to avoid adoption costs. We find that the optimal policy follows a simple structure and induces part-time efforts, rather than the maximal effort reported in previous studies. In particular, the regulator should offer no subsidy before the arrival of a technology report, provide a one-time subsidy contingent upon that report, and always set a termination deadline. At the deadline, the firm is forced to select an external option that is associated with social costs. The optimal report-based subsidy decreases with time. Under the optimal policy, the firm works until an effort deadline, makes no effort thereafter, and reports the technology as soon as it arrives. This study also characterizes the necessary and sufficient conditions under which the optimal policy reduces to one that leads, in terms of throughout time, to effort that is maximal or minimal. Our results indicate that policymakers should implement a policy that compensates firms more in the present and less in the future.     

火灾安全评价方法研究

火灾安全评价是利用系统工程的方法对拟建或已有工程、系统可能存在的危险性及可能产生的后果进行综合评价和预测,并根据可能导致的火灾事故风险的大小,提出相应的安全对策措施,以达到工程、系统安全的过程。主要论述了火灾安全评价的目的、火灾安全评价的意义、火灾安全评价的一般程序、火灾安全评价方法选择、火灾安全评价方法的比较及火灾安全评价方法在消防中应用。     

基于模糊综合评判的地空导弹阵地选择

在现代防空中,由于精确制导技术在空袭兵器当中的运用,使防空作战中兵力机动显得格外重要.为实现机动作战,阵地选择就成为机动作战中的重要环节.运用模糊数学原理和方法,结合地空导弹部队阵地选择的特点,给出了阵地选择评价因素指标体系,建立了阵地选择方案的二级模糊综合评判模型,并采用层次分析法(AHP)对阵地选择评价因素的权重进行了确定,最终得出阵地选择合理的评价结果.     

基于DS/AHP的导弹发射阵地选择方法

战术导弹发射阵地选择是导弹作战兵力运筹的重要组成部分,其本质是一多准则多属性决策问题。传统的层次分析法无法明确描述这类问题中所蕴涵的不确定性,通过DS证据理论的引入,研究了战术导弹发射阵地选择的DS/AHP方法,应用实例说明了该方法的可行性和有效性。     

基于GQM的装备软件可靠性参数选取方法

针对装备软件无可靠性定量要求以及开发过程缺少监管的问题,提出基于GQM(Goal-Question-Metric)的装备软件可靠性参数选取方法。首先构建了软件可靠性通用参数集和装备软件可靠性特有参数集,然后按照GQM方法的框架,从不同角度出发,制定装备软件可靠性度量目标,列出为实现目标需要回答的一系列问题,进而以回答问题的方式,确定不同情况下适用的软件可靠性参数,最终建立装备软件可靠性参数体系。     

基于群决策协同网络信息的掩护机编队选择

针对任务机群中掩护机编队的选择,用群决策协同网络信息模型进行了掩护机编队的选择。首先,给出了协同网络、模糊数和语言变量的相关概念;其次,分析了掩护机编队选择的指标体系框架和协同网络信息框架;然后,构建了群决策协同网络信息的数学模型,在此基础上,给出了方案选择的步骤;最后,运用该模型对掩护机编队的选择进行求解。结果表明：该模型能够综合群体专家的知识,解决掩护机编队选择中的定性判断问题。该模型可用于个体指标和协同指标均为定性指标时的方案优选问题。     

地球静止轨道高能电子通量在线预测模型研究

利用粒子群优化算法和最小二乘支持向量机，建立了地球静止轨道高能电子通量(1.8-3.5MeV)在线预测模型。针对粒子群优化算法，提出了一种新的粒子群多样性测度计算方法，有效改善了其早熟收敛现象；基于改进的粒子群优化算法优化最小二乘支持向量机的正则化参数和核参数；利用滑动时间窗口策略更新模型数据，设计变量选择触发机制以及模型的再学习机制实现模型的在线预测功能。[根据题目的调整，对摘要做了相应改动]通过对2000年电子通量监测数据和相关太阳风、地磁参数等实际数据进行提前1-3天的预测实验，表明了所建在线预测模型具有较高的预测性能，有一定的实用价值。     

Information theory for ranking and selection

We study the classical ranking and selection problem, where the ultimate goal is to find the unknown best alternative in terms of the probability of correct selection or expected opportunity cost. However, this paper adopts an alternative sampling approach to achieve this goal, where sampling decisions are made with the objective of maximizing information about the unknown best alternative, or equivalently, minimizing its Shannon entropy. This adaptive learning is formulated via a Bayesian stochastic dynamic programming problem, by which several properties of the learning problem are presented, including the monotonicity of the optimal value function in an information-seeking setting. Since the state space of the stochastic dynamic program is unbounded in the Gaussian setting, a one-step look-ahead approach is used to develop a policy. The proposed policy seeks to maximize the one-step information gain about the unknown best alternative, and therefore, it is called information gradient (IG). It is also proved that the IG policy is consistent, that is, as the sampling budget grows to infinity, the IG policy finds the true best alternative almost surely. Later, a computationally efficient estimate of the proposed policy, called approximated information gradient (AIG), is introduced and in the numerical experiments its performance is tested against recent benchmarks alongside several sensitivity analyses. Results show that AIG performs competitively against other algorithms from the literature.     

基于模糊聚类方法的机场目标选择模型

在现代战争中,机场作为一个战略级别的目标,要发挥其整体的作用需要目标群中的每个子目标都能最大限度地相互配合,使其本身的价值充分地体现出来.针对当前在目标选择上片面的问题,根据模糊聚类方法的基本原理,结合机场本身的特征进行改进,构建了机场目标选择模型,通过计算,证明可以克服以往目标打击方案界定的不明确性,避免了选择目标的单一化.