Group testing procedures with quantitative features and incomplete identification

We present a group testing model for items characterized by marker random variables. An item is defined to be good (defective) if its marker is below (above) a given threshold. The items can be tested in groups; the goal is to obtain a prespecified number of good items by testing them in optimally sized groups. Besides this group size, the controller has to select a threshold value for the group marker sums, and the target number of groups which by the tests are classified to consist only of good items. These decision variables have to be chosen so as to minimize a cost function, which is a linear combination of the expected number of group tests and an expected penalty for missing the desired number of good items, subject to constraints on the probabilities of misclassifications. We treat two models of this kind: the first one is based on an infinite population size, whereas the second one deals with the case of a finite number of available items. All performance measures are derived in closed form; approximations are also given. Furthermore, we prove monotonicity properties of the components of the objective function and of the constraints. In several examples, we study (i) the dependence of the cost function on the decision variables and (ii) the dependence of the optimal values of the decision variables (group size, group marker threshold, and stopping rule for groups classified as clean) and of the target functionals (optimal expected number of tests, optimal expected penalty, and minimal expected cost) on the system parameters.© 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

基于协同交战的战术数据链技术研究

介绍了外军典型战术数据链的发展情况,同时根据未来网络化作战需求,对基于协同交战的战术数据链的作战使用进行了研究,提出了基于协同交战的战术数据链体系结构、功能需求和指标需求,最后给出了基于协同交战的战术数据链的发展建议.     

指挥与控制装备技术发展趋势

研究分析了指挥与控制装备技术的发展趋势,并对具有重要影响指控发展的前沿技术作出了分析,最后对大数据技术作了概述,指出了在指挥控制装备中应用的可能性。     

再生分辨矩阵与决策熵的不完备决策系统属性约简

为了有效地解决不完备决策系统的属性约简问题,提高属性约简的效率,提出了基于再生分辨矩阵与决策熵的不完备属性约简算法。该算法利用基于容差关系的分辨矩阵来计算相对核,通过再生分辨矩阵计算再生集和再生集属性来缩小加入约简集的条件属性选择范围,以再生集属性的分辨度和决策熵为依据,选择加入约简集的条件属性,并通过实例进行验证分析。结果表明,该算法适用于协调不完备决策系统与不协调不完备决策系统,能够有效地降低时间复杂度,并得到最优属性约简。     

基于动态窗口的灰色加权填充算法及应用?

为解决复杂系统中单属性缺失数据填充困难问题,提出了基于动态窗口的灰色加权填充算法。该算法通过建立双向灰色预测模型,并采用模型精度评价系数加权填充缺失数据,有效增强了算法的准确性;提出基于灰色模型评价系数反馈的动态伸缩窗口概念,寻找产生最优模型的训练数据序列,使算法具有良好的鲁棒性和适应性。实验结果表明,该方法在RMSE和MA两项指标上均优于传统的双向灰插值、灰插值、多项式插值等方法。     

基于数据挖掘的战场目标综合识别技术

分析了现有战场目标识别技术存在的问题,提出了基于数据挖掘的战场目标综合识别总体框架,对目标识别知识表示、目标特征知识挖掘、作战模式知识挖掘以及目标综合识别智能化推理等关键技术进行了研究,并说明了各关键技术在战场目标识别中的应用示例,可为提高战场目标识别的自动化、智能化水平提供借鉴。     

多样化军事任务异构数据集成应用方法

为实现多源异构作战数据高效融合共享,提出了改进型中间件异构数据集成框架,设计了作战数据融合运用核心组件,实现了多源异构作战数据综合应用平台,提高了各类作战数据的融合运用效率,为指挥员及时掌握战场态势,高效科学决策提供了数据支撑。     

Monitoring censored lifetime data with a weighted‐likelihood scheme

Lifetime experiments are common in many research areas and industrial applications. Recently, process monitoring for lifetime observations has received increasing attention. However, some existing methods are inadequate as neither their in control (IC) nor out of control (OC) performance is satisfactory. In addition, the challenges associated with designing robust and flexible control schemes have yet to be fully addressed. To overcome these limitations, this article utilizes a newly developed weighted likelihood ratio test, and proposes a novel monitoring strategy that automatically combines the likelihood of past samples with the exponential weighted sum average scheme. The proposed Censored Observation‐based Weighted‐Likelihood (COWL) control chart gives desirable IC and OC performances and is robust under various scenarios. In addition, a self‐starting control chart is introduced to cope with the problem of insufficient reference samples. Our simulation shows a stronger power in detecting changes in the censored lifetime data using our scheme than using other alternatives. A real industrial example based on the breaking strength of carbon fiber also demonstrates the effectiveness of the proposed method. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 631–646, 2017     

基于数据场的作战单元价值评估模型

作战单元价值是目标选择的重要依据。根据作战单元在作战体系中的效用和影响,提出作战单元的属性价值和级联价值及其量化方法,利用层次分析法和数据场理论,分别评估作战单元的属性价值和级联价值,建立作战单元价值评估模型,并进行仿真分析,验证该评估模型的有效性。     

炮瞄雷达试验数据处理中有关问题的探讨

结合炮瞄雷达国家军用标准和靶场炮瞄雷达试验,对炮瞄雷达精度试验数据处理中的误差分组统计方法、样本大小选取和异常数据点处理等问题进行了探讨,并且提出了相应的处理方法