基于云重心评判法的炮兵指挥训练水平评估*

炮兵指挥训练水平指标体系中,既有精确数值型表示的,又有语言值来描述的,给评估指标的数据处理带来了一定的困难。云重心评判法能较好地处理该类既有定性指标,又有定量指标的综合评价问题。构建了炮兵师(旅)指挥训练水平评估体系,详细介绍了运用云重心评判法来实现炮兵指挥训练水平评估的具体步骤。结合指挥决策指标体系实例,验证了该方法的有效。该方法具有一定的推广意义。     

Parallel machine scheduling with eligibility constraints: A composite dispatching rule to minimize total weighted tardiness

We study a parallel machine scheduling problem, where a job j can only be processed on a specific subset of machines M_j, and the M_j subsets of the n jobs are nested. We develop a two‐phase heuristic for minimizing the total weighted tardiness subject to the machine eligibility constraints. In the first phase, we compute the factors and statistics that characterize a problem instance. In the second phase, we propose a new composite dispatching rule, the Apparent Tardiness Cost with Flexibility considerations (ATCF) rule, which is governed by several scaling parameters of which the values are determined by the factors obtained in the first phase. The ATCF rule is a generalization of the well‐known ATC rule which is very widely used in practice. We further discuss how to improve the dispatching rule using some simple but powerful properties without requiring additional computation time, and the improvement is quite satisfactory. We apply the Sequential Uniform Design Method to design our experiments and conduct an extensive computational study, and we perform tests on the performance of the ATCF rule using a real data set from a large hospital in China. We further compare its performance with that of the classical ATC rule. We also compare the schedules improved by the ATCF rule with what we believe are Near Optimal schedules generated by a general search procedure. The computational results show that especially with a low due date tightness, the ATCF rule performs significantly better than the well‐known ATC rule generating much improved schedules that are close to the Near Optimal schedules. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 249–267, 2017     

基于多侦察资源的电子侦察作战效能评估模型

现代战争战场环境越来越复杂,准确发现目标的难度越来越大,靠单侦察设备独立完成侦察任务已难以满足作战需要。通过建立多侦察资源的电子对抗侦察效能评估模型,对来自同一作战平台的不同侦察设备和来自不同平台的侦察设备的数据进行融合,最大限度地发挥各侦察设备的作战效能,为决策者提供作战使用依据。     

基于混合数据挖掘模型预测用户流失

用户流失预测问题广泛应用在银行、金融、电信等多种领域。对用户行为进行有效的预测和分析有助于企业的竞争和了解瞬息万变的市场规律。采用3种混合的数据挖掘模型对用户流失问题进行了研究,以形成一个准确高效的用户流失预测模型。这3种模型应用于数据挖掘的两个阶段:聚类阶段和预测分析阶段。在第1阶段中,对用户的数据进行过滤。第2阶段对用户行为进行预测。第1个模型采用了二分k-means算法进行数据过滤和多层感知人工神经网络(MLP-ANN)相结合进行预测。第2个模型采用层次化聚类与MLP–ANN相结合进行预测。第3个模型使用自组织映射(Self-Organizing Maps)与MLP-ANN进行预测。这3种模型预测分析基于真实数据,用户流失率采用3种模型混合计算的方式得出结果并同真实值进行比较。分析结果表明采用多模型的混合数据挖掘模型的数据准确度优于普通的单一模型。     

Rényi信息增量和协方差联合控制的多传感器管理算法

针对目标跟踪中雷达组网场景下多传感器管理问题,结合Rényi信息增量和协方差两种算法各自特性,利用并行处理的思想提出了一种基于Rényi信息增量和协方差联合控制的传感器管理算法。在具体仿真设计环节,分为传感器跟踪能力大于目标数和传感器跟踪能力小于目标数两种场景。仿真结果表明该算法在单目标匀速、多目标匀加速等多数场景下能够对目标进行有效跟踪,同时降低了传感器的切换频率,具有更好的实时性。     

多雷达观测信号融合检测算法

针对海上小目标检测问题提出了一种基于多雷达观测信号层融合的检测算法。该算法对各个雷达的观测值按采样时刻进行排序,然后根据对应时刻的脉冲信号进行高阶互累积量计算然后在相关域上积累进行似然比检测。仿真分析表明该算法与基于贝叶斯准则的分布式检测算法相比,具有较低的复杂度和低信噪比条件下较高的目标检测概率。     

面向多目标跟踪的PHD滤波多传感器数据融合算法

针对密集杂波环境下单传感器应用高斯混合PHD算法进行多目标跟踪时性能下降的问题,提出一种面向多目标跟踪的PHD滤波多传感器数据融合算法。首先构建了基于高斯混合PHD滤波的多传感器数据融合系统框架,各传感器利用高斯混合PHD滤波算法进行局部状态估计,然后对各传感器的状态估计结果进行关联度计算,最后通过构建自适应混合参数,引入协方差交叉算法对关联状态进行融合。仿真实验表明,与单传感器高斯混合PHD多目标跟踪算法相比,所提算法有效提高了目标数量和状态的估计精度。     

Does military expenditure increase external debt? Evidence from Asia

This article empirically explores the effect of military spending on external debt, using a sample of ten Asian countries over the years from 1990 to 2011. The Hausman’s test suggests that the random-effects model is preferable; however, both random-effects and fixed-effects models are used in this research. The empirical results show that the effect of military spending on external debt is positive, while the effects of foreign exchange reserves and of economic growth on external debt are negative. For developing countries caught in security dilemma, military expenditure often requires an increase in external debt, which may affect economic development negatively.     

图像标注研究及其在情报处理中的应用

图像数据具有直观、信息量丰富等特点。图像标注方法通过获取图像特征,训练语言模型,实现用自然语言自动描述图像信息。简要介绍了图像标注方法的分类及其相关关键技术。研究表明,通过对大规模图像的自动描述,能更好地管理、分析海量图像信息,能高效地对图像进行分类、检索。结合特定的信息处理技术,图像标注可用于发现有价值的情报信息,为国防安全、战略决策等提供信息支撑。     

美国陆军数据战略目标及实施

为深入研究美陆军数据战略目标及实施策略,为我军数据战略研究提供借鉴,文章对美陆军2016年发布的最新《陆军数据战略》进行分析,指出其目标是实现数据的可视化、可获取、可信任、可理解和互操作,并对美陆军数据战略的具体实施策略进行了剖析,指出美国陆军数据战略推动的是美军军事作战理论转型,从"网络为中心"转变为以"数据为中心"作战理念,其核心意图在于以数据优势实现指挥决策优势。