系统评估效度分析的定量化方法

系统评估效度的定量化分析是评估后检验的有效方法,对于判断评估方法的相容性、评估结果的合理性具有重要意义。研究了等级相关系数法、兼容度优化法、肯德尔和谐系数法和模糊聚类法等4种效度分析方法的原理和步骤,分析了各种效度分析方法的优缺点,并通过实例验证了4种方法分析结果的一致性。     

海洋环境影响航母编队反潜效能的三级评估模型*

针对海洋环境影响航母编队作战效能的评估问题,采用层次分析法分析了影响编队效能的海洋环境因子,以美军航母战斗群为例给出了经典航母编队的体系结构,并以该编队结构体系中反潜效能为例,建立了海洋环境影响的三级评估模型。研究思想对航母编队的效能评估有一定参考意义。     

基于主成分法的侦察雷达系统效能评价*

为评估雷达系统的效能优劣,应用主成分分析法建立雷达系统效能评估模型,引入施密特正交法对原始数据进行预处理,解决了由于指标间的多重相关性导致的结果失真问题,并以某型雷达及其三种改进型的系统效能评估为例,进行了实例仿真,为评估和改进现有侦察雷达的效能提供了参照。     

基于改进AHP与集对分析法的防空兵群阵地选择

防空兵群阵地选择是防空兵力部署的前提条件,阵地选择与配置的正确与否是防空兵部队能否有效进行抗击敌空袭兵器的一个重要因素.在分析以往防空阵地优选方法不足的基础上,提出了基于改进的层次分析与集对分析的多因素优选方法,建立了防空兵群配置地域方案优选的模型.通过实例分析了影响防空兵群阵地选择的相关因素,确定了配置地域优选的指标体系,用三标度法确定指标因素的权重,以相对贴近度的大小对待选阵地进行优选和排序.该方法能够定性与定量相结合,模型简单规范,为防空兵群阵地优选提供了一种有效的方法和途径.     

数据挖掘在图像信息隐写分析中的应用

提出数据挖掘在图像信息隐写分析中的应用。首先计算原始图像和隐写图像在通用图像质量指标下的失真测度,然后利用数据挖掘技术建立一个预测模型,完成失真测度到已知隐写概率的映射,模型的输出即为预测隐写概率。实验结果表明,使用该方法得到的预测隐写概率和已知隐写概率的相关度,当使用训练样本时达到0.951以上,使用测试样本时达到0.943以上,达到了很好的预测效果。     

一种面向频域的通信信号盲干扰检测算法

针对低干信比和复杂动态情况下传统的干扰检测算法效率不高的问题,提出一种基于盲通信信号频域处理的未知干扰自动检测算法。该方法首先借助快速独立成份分析(FICA)从频谱差分数据中分离干扰和通信信号成份分量,然后利用各分量的峰度作为干扰与通信信号的识别特征检测干扰。实验结果表明,此算法能有效地在干信比小于5 dB的情况下从盲通信信号背景中自动提取未知干扰的信息,实现高精度地盲干扰检测。     

基于S变换的跳频信号参数估计

对跳频信号的时频域进行分析和参数估计是识别、跟踪及干扰跳频信号的重要基础。针对接收到的未知任何先验参数的跳频信号,提出了一种基于S变换(S-transform)的跳频信号参数估计算法,通过S变换,能正确估计出跳频信号的跳频周期、跳变时刻及跳频图案。仿真结果表明,与平滑伪Wigner-Ville分布(SPWVD)进行比较,该算法能够在低信噪比条件下,在时频域中有较好的解析能力,提高了跳频信号参数估计的准确性。     

磁致伸缩扭转导波小管径弯管检测

针对扭转导波对小管径弯管的检测问题,分别采用数值模拟和实验方法进行研究。使用ANSYS软件模拟扭转导波在弯管中的传播;设计一种针对小管径管道的磁致伸缩扭转导波检测传感器,并对弯管进行检测,建立该传感器的导波激发和接收模型,利用理论模型对实验信号进行解读。研究结果表明:T(0,1)模态导波在小管径管道弯头处发生模态转换,部分T(0,1)模态转换成F(1,1)模态,F(1,1)模态具有方向性,垂直于弯头拱背-拱腹方向;模态转换会造成检测信号的双端面反射现象,第二个端面回波与第一个端面回波幅值比随频率的增大呈减小趋势;传感器激发出的纵向磁致伸缩力会导致实验信号中出现少量纵向模态导波。研究结论为磁致伸缩扭转导波对小管径弯管的检测提供理论指导。     

Steady‐state diffusion approximations for discrete‐time queue in hospital inpatient flow management

In this article, we analyze a discrete‐time queue that is motivated from studying hospital inpatient flow management, where the customer count process captures the midnight inpatient census. The stationary distribution of the customer count has no explicit form and is difficult to compute in certain parameter regimes. Using the Stein's method framework, we identify a continuous random variable to approximate the steady‐state customer count. The continuous random variable corresponds to the stationary distribution of a diffusion process with state‐dependent diffusion coefficients. We characterize the error bounds of this approximation under a variety of system load conditions—from lightly loaded to heavily loaded. We also identify the critical role that the service rate plays in the convergence rate of the error bounds. We perform extensive numerical experiments to support the theoretical findings and to demonstrate the approximation quality. In particular, we show that our approximation performs better than those based on constant diffusion coefficients when the number of servers is small, which is relevant to decision making in a single hospital ward.     

Aggregating courier deliveries

We consider the problem of efficiently scheduling deliveries by an uncapacitated courier from a central location under online arrivals. We consider both adversary‐controlled and Poisson arrival processes. In the adversarial setting we provide a randomized (3βΔ/2δ ? 1) ‐competitive algorithm, where β is the approximation ratio of the traveling salesman problem, δ is the minimum distance between the central location and any customer, and Δ is the length of the optimal traveling salesman tour overall customer locations and the central location. We provide instances showing that this analysis is tight. We also prove a 1 + 0.271Δ/δ lower‐bound on the competitive ratio of any algorithm in this setting. In the Poisson setting, we relax our assumption of deterministic travel times by assuming that travel times are distributed with a mean equal to the excursion length. We prove that optimal policies in this setting follow a threshold structure and describe this structure. For the half‐line metric space we bound the performance of the randomized algorithm in the Poisson setting, and show through numerical experiments that the performance of the algorithm is often much better than this bound.