基于依赖矩阵的Web服务组合故障诊断

为了保证指挥信息系统在动态环境下能够提供持续可靠的组合服务,提出一种利用依赖矩阵对Web服务组合故障原因进行诊断的模型,对依赖矩阵的建立进行了详细说明。然后,基于构造的依赖矩阵,提出改进的贪心算法对失效情况进行探测,并设计了基于二分查找的故障定位算法。实验模拟表明,提出的模型能够利用少量探测就能监测整个服务组合流程的运行情况,并定位找到错误源。     

New results on rendezvous search on the interval

In a rendezvous search problem, two players are placed in a network and must try to meet each other in the least possible expected time. We look at rendezvous search on a discrete interval in which the players are initially placed using independent draws (usually assumed to be from the same distribution). Some optimal solutions are known if this distribution is uniform, and also for certain other special types of distribution. In this article, we present two new results. First, we characterize the complete set of solutions for the uniform case, showing that all optimal strategies must have two specific properties (namely, of being swept and strictly geodesic). Second, we relate search strategies on the interval to proper binary trees, and use this correspondence to derive a recurrence relation for solutions to the symmetric rendezvous problem for any initial distribution. This relation allows us to solve any such problem computationally by dynamic programming. Finally, some ideas for future research are discussed. © Wiley Periodicals, Inc. Naval Research Logistics 60: 454–467, 2013     

基于立方体理论的MFTA软件设计与实现

本文报道的MFTA(Multi-stateFaultTreeAnalysis)软件为可靠性工程师分析多状态系统提供一种计算机辅助分析工具。我们设计了友好的Windows95用户交互界面 ,采用树视图组件实现逻辑树结构框架的输入 ,采用字符串表格组件实现判定表的直接输入 (立方体形式的 0 -1序列 ) ,还实现了多态单调关联典型结构函数到立方体形式判定表的转化。以标准模板库 (StandardTemplateLibrary)为基础 ,采用面向对象程序设计方法构建了立方体类库 ;然后 ,实现了以立方体理论为核心的MFTA定性定量分析算法 ,完成了软件的研制。     

电子稳像中运动矢量一致性的优化算法

针对电子稳像技术传统块匹配法求运动矢量的固有缺点,采取四叉树———一种变块匹配方法计算运动矢量,使求得的运动矢量有较好的一致性.与其它变块匹配方法相比,该方法克服了其它变块匹配法的不足.实验表明,使用该法求出的运动矢量有较好的一致性和准确性.     

Multi-scale traffic vehicle detection based on faster R-CNN with NAS optimization and feature enrichment

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is compara-tively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R-CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R-CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the imple-mentation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.     

自航式鱼雷发射装置发射管长度优化研究

基于某型鱼雷自航发射的内弹道数学模型,选择自航管的总长度作为优化目标,讨论了约束函数的取值,确定了优化问题的数学表达.采用惩罚函数法进行寻优计算,针对约束函数具有不可微和非线性的特点,采用模式搜索算法进行了无约束优化的求解,给出了优化结果并进行了比较.     

Bayesian analysis of queues with impatient customers: Applications to call centers

Queuing models have been extensively used in the literature for obtaining performance measures and developing staffing policies. However, most of this work has been from a pure probabilistic point of view and has not addressed issues of statistical inference. In this article, we consider Bayesian queuing models with impatient customers with particular emphasis on call center operations and discuss further extensions. We develop the details of Bayesian inference for queues with abandonment such as the M/M/s + M model (Erlang‐A). In doing so, we discuss the estimation of operating characteristics and its implications on staffing. We illustrate the implementation of the Bayesian models using actual arrival, service, and abandonment data from call centers. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

海洋移动目标多模型运动预测方法

分析海洋移动目标的运动特征,提出了预测前插值的灰色预测方法,改进了航迹变更预测和潜在区域预测模型。通过集成匀速运动预测、航迹变更预测、基于航迹的预测和潜在区域预测,提出多模型运动预测方法及其模型参数配置依据,根据滑动时间窗口中的观测数据与预测值的统计比较,评价不同预测方法的近期预测效果,决策下阶段适宜选择的预测方法。仿真实验表明多模型运动预测比使用单一运动预测方法降低预测风险,提高了预测精度。     

驱护舰编队对潜防御性搜索态势分析与方法

针对驱护舰武器装备的发展,结合驱护舰编队海上对潜防御作战的新特点,根据特定驱护舰编队的使命任务,提出了特定驱护舰编队对潜进攻性搜索与防御性搜索的新概念,并在战斗战场范围内对特定驱护舰编队对潜防御性搜索态势进行了分析,给出了编队对潜防御性搜索方法.对部队作战与训练具有一定的参考应用价值.     

故障树近似计算中最优权因子的选取

在故障树近似计算时,探讨通过加权提高计算准确度的简便方法。根据底事件发生概率的不同,利用VisualC 语言进行蒙特卡罗仿真计算,得到了在近似计算故障树顶事件发生概率时,在不同底事件发生概率对应区间内的最优权因子。利用该方法得到的最优权因子可以提高故障树近似计算的准确度,尤其是在当底事件发生概率较大时,其效果更为明显,可较好地满足采用故障树对某些特殊设备进行顶事件发生概率计算时提高计算精度的需求。