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     

基于多特征模糊融合的疲劳状态判决

在基于视觉的疲劳驾驶识别过程中,使用单个特征进行疲劳驾驶判断,常常会受到非普遍适用性、噪声等因素的影响,从而导致识别率降低。为了解决眼部特征参数或者是嘴巴特征参数单个特征识别率低甚至特使环境无法识别的问题,提出一种基于多特征融合的判决方法,利用了各种特征之间的优势互补,可以降低噪声和类内类间差异的影响,从而提高系统的性能,并且能增强适用性。最后通过实验结果证明,使用眼部和嘴巴特征融合的方法比单一的判决方法准确率更高。     

Military expenditure and economic growth in Middle Eastern countries and Turkey: a non-linear panel data approach

The economic growth effects of military expenditure have been the subject of a large literature in defence economics. Theories on the economic impacts of military expenditure greatly differ and include arguments that they either enhance economic growth or crowd out productive investments. Empirical literature on defence expenditure and economic growth nexus generally employs linear specifications to investigate the impact of defence expenditures on economic growth. Although it is now well established that many economic variables may have a non-linear data-generating mechanism, it seems that this reality has long been neglected in empirical work on defence–growth nexus. This paper attempts to fill this gap by employing non-linear panel data models to examine the effects of military expenditures on economic growth for Middle Eastern countries and Turkey, for the time period 1988–2012. Results show that the effect of military expenditure on economic growth is nonlinear such that the state of the economy actually determines the effect of the former on the latter. This is important not only in showing asymmetric relationship between these variables but also in revealing the reasons of mixed results of earlier literature.     

The role of covariate balance in observational studies

Observational data are prevalent in many fields of research, and it is desirable to use this data to make causal inferences. Because this data is nonrandom, additional assumptions are needed in order to construct unbiased estimators for causal effects. The standard assumption is strong ignorability, though it is often impossible to achieve the level of covariate balance that it requires. As such, researchers often settle for lesser balance levels within their datasets. However, these balance levels are generally insufficient to guarantee an unbiased estimate of the treatment effect without further assumptions. This article presents several extensions to the strong ignorability assumption that address this issue. Under these additional assumptions, specific levels of covariate balance are both necessary and sufficient for the treatment effect estimate to be unbiased. There is a trade‐off, however: as balance decreases, stronger assumptions are required to guarantee estimator unbiasedness. These results unify parametric and nonparametric adjustment methods for causal inference and are actualized by the Balance Optimization Subset Selection framework, which identifies the best level of balance that can be achieved within a dataset. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 323–344, 2017     

Performance analysis of the cultural and creative industry: a network‐based approach

The cultural and creative industries (CCIs) in Taiwan have gradually contributed to the national economy under the impetus of government policies. We employ a two‐stage data envelopment analysis model with an additive efficiency decomposition approach to measure the profitability and marketability of 22 Taiwanese cultural and creative companies. Furthermore, we employ the network‐based ranking approach to identify benchmark inputs/outputs, and the strengths and weakness of each company. Our empirical results show that the profitability of the cultural and creative companies is better than their marketability. Companies in the industries of publishing, creative life, popular music, and cultural content averagely perform better than those in the other three types of CCIs in terms of profitability. Companies in the creative life industry are on average more efficient than those in the other five types of CCIs in terms of marketability. The profitability/marketability matrix of cultural and creative companies is also presented.