函数变换提高灰色预测模型精度的条件

指出选择函数变换来提高模型精度主要与三个方面的因素有关：提高数据序列的光滑比、调整数据序列的级比和确保凸凹性。在调整级比方面，扩充了级比压缩变换的相关定理，并讨论了几种常用的函数变换在上述三个方面的关系。最后结合实例提出，对于变换后的数据序列若不满足这三方面的要求可以再进行函数变换以达到提高模型精度的目的。     

基于度量元的静态软件缺陷预测技术

软件缺陷预测技术是当前软件工程领域的一个热点研究问题。回顾和综述了基于度量元的静态软件缺陷预测技术研究的起源与国内外最新进展动态,并对常用缺陷预测技术的评价指标进行对比和分析,指出其优缺点和适用范围。最后对静态软件缺陷预测技术的可能发展方向进行预测。     

火控系统故障预测与健康管理技术

故障预测和健康管理(PHM)技术具有故障诊断、故障预测以及健康管理的功能,对降低火控装备维修成本、增强火控系统的完备性以及提高火控系统管理效率具有重要意义。根据通用火控系统发展现状及应用需求,将PHM技术引入到火控系统中。首先介绍了PHM技术原理和国内外发展现状,重点讨论了PHM关键技术和通用火控系统PHM体系结构。最后展望了火控系统PHM技术的发展趋势。     

基于流程仿真的物资接收系统可靠性预计方法

针对船舶物资接收时间计算的问题,新增加了对设备发生故障的考虑,通过引入接收时间可靠性的概念,将其转换为船舶物资接收系统的可靠性预计问题。为了解决上述可靠性预计问题,提出了基于流程仿真的系统可靠性预计方法。分析了物资接收系统的工作流程,依据工作流程实现了仿真程序,用蒙特卡洛法对物资接收系统的可靠性进行了求解,并分析了设备不同的可靠性水平对物资接收系统可靠性的影响。仿真结果表明,增加了对设备故障的考虑后,对物资接收时间的估计更加接近实际;基于流程仿真的系统可靠性预计方法的模型更容易理解,所得结论更加具体。     

The human consequences of foreign military intervention

The empirical international conflict literature has given much recent attention to interstate armed force’s impact on human well-being. While empirical research has advanced our understanding of the phenomenon considerably, we argue that one conclusion that many studies have reached is preliminary. Some recent research contends that only full-scale war, and not force short of war, has a discernable impact on human welfare or physical quality of life (PQOL). We develop theory on one type of force short of war, large-scale foreign military intervention (FMI), and its potential effects on PQOL. Using interrupted time series and panel corrected standard error methodologies, we find that from 1960 to 2005 large-scale FMI had a statistically and substantively significant impact on the PQOL of populations in 106 developing countries. The specific effect that this type of armed force has depended in large part on the regime type of the target country.     

电传动装甲车辆负载功率预测实时能量管理策略

针对电传动装甲车辆负载功率预测功能缺失导致控制作用滞后的问题,提出一种具有较高负载功率预测精度的实时能量管理策略。在分析整车结构的基础上,采用理论分析和数据拟合方法,建立各动力源数学模型。将差分自回归移动平均模型和自适应马尔可夫链两种预测方法相结合,设计非平稳趋势性负载功率组合预测方法。在非线性模型预测控制框架下,构建多目标优化函数,采用序列二次规划法在有限时域内实时求解最优控制指令,优化多动力源协调控制过程。依托硬件在环仿真平台进行多路面行驶实验,对比有无功率预测的能量管理控制效果。结果表明,改进的实时能量管理策略对未来负载功率具有较好的预见性,能够显著优化多动力源协调控制过程,提升车辆燃油经济性,稳定母线电压和电池荷电状态,对传统模型预测控制下的工程应用场景具有一定借鉴意义。     

The SSA-BP-based potential threat prediction for aerial target considering commander emotion

The target's threat prediction is an essential procedure for the situation analysis in an aerial defense system. However, the traditional threat prediction methods mostly ignore the effect of commander's emotion. They only predict a target's present threat from the target's features itself, which leads to their poor ability in a complex situation. To aerial targets, this paper proposes a method for its potential threat prediction considering commander emotion (PTP-CE) that uses the Bi-directional LSTM (BiLSTM) network and the backpropagation neural network (BP) optimized by the sparrow search algorithm (SSA). Furthermore, we use the BiLSTM to predict the target's future state from real-time series data, and then adopt the SSA-BP to combine the target's state with the commander's emotion to establish a threat prediction model. Therefore, the target's potential threat level can be obtained by this threat prediction model from the predicted future state and the recognized emotion. The experimental results show that the PTP-CE is efficient for aerial target's state prediction and threat prediction, regardless of commander's emotional effect.     

Stochastic framework for partially degradation systems with continuous component degradation‐rate‐interactions

Many conventional models that characterize the reliability of multicomponent systems are developed on the premise that for a given system, the failures of its components are independent. Although this facilitates mathematical tractability, it may constitute a significant departure from what really takes place. In many real‐world applications, system components exhibit various degrees of interdependencies, which present significant challenges in predicting degradation performance and the remaining lifetimes of the individual components as well as the system at large. We focus on modeling the performance of interdependent components of networked systems that exhibit interactive degradation processes. Specifically, we focus on how the performance level of one component affects the degradation rates of other dependent components. This is achieved by using stochastic models to characterize how degradation‐based sensor signals associated with the components evolve over time. We consider “Continuous‐Type” component interactions that occur continuously over time. This type of degradation interaction exists in many applications, in which interdependencies occur on a continuum. We use a system of stochastic differential equations to capture such “Continuous‐Type” interaction. In addition, we utilize a Bayesian approach to update the proposed model using real‐time sensor signals observed in the field and provide more accurate estimation of component residual lifetimes. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 286–303, 2014     

基于灰色神经网络的装甲部队油料消耗预测

油料消耗量的精确预测直接影响装甲部队后勤保障能力的提升,而传统预测模型精度不高,应用范围也有一定的局限,难以满足信息化战争精确保障的需要。提出一种装甲部队油料消耗预测的组合模型,对历史油料消耗数据和油耗影响因素进行统计分析,求出各影响因素与油耗量的关联度作为权重系数;通过改进GM(1,1)模型预测某部队下一次军事行动的油耗量;用GM(1,1)模型的预测值、加权后的各影响因素值和油耗实际值训练网络,对下一次想定的军事行动油耗量进行预测。通过平均相对误差计算表明,组合预测模型比单一的GM(1,1)模型预测精度高,能够较好地指导部队进行下一步的油料供管工作。     

单站单圈卫星初轨确定方法研究

为实现低轨卫星轨道的快速确定和预报,基于单站单圈雷达站测量数据采用遗传算法和最小二乘法对卫星初轨确定及轨道预测问题进行了研究。通过比较分析不同观测误差下两种方法的仿真结果,验证了初轨确定过程中两种方法的可行性,同时指出了各自的优缺点和适用条件,为不同观测条件下卫星最优初轨确定的方法提供了参考。