Bayesian testing strategies for software with an operational profile

We consider a software reliability model where the failure rate of each fault depends on the specific operation performed. The software is tested in a given sequence of test cases for fixed durations of time to collect data on failure times. We present a Bayesian analysis of software failure data by treating the initial number of faults as a random variable. Our analysis relies on the Markov Chain Monte Carlo methods and is used for developing optimal testing strategies in an adaptive manner. Two different models involving individual and common faults are analyzed. We illustrate an implementation of our approach by using some simulated failure data. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:747–763, 2001     

基于模糊推理的目标对潜发现问题研究

基于模糊推理基本思想,针对潜艇水下收集目标信息的特点,在目标对潜艇威胁信息存在不确定性因素的基础上,建立了判断潜艇被发现与否的指标体系,应用模糊推理方法建立了判断规则,并给出了推导过程和实现方式,在把模糊推理方法应用于潜艇威胁判断模型的研究上做了初步尝试。     

The effect of training data set size and the complexity of the separation function on neural network classification capability: The two-group case

Classification among groups is a crucial problem in managerial decision making. Classification techniques are used in: identifying stressed firms, classifying among consumer types, and rating of firms' bonds, etc. Neural networks are recognized as important and emerging methodologies in the area of classification. In this paper, we study the effect of training sample size and the neural network topology on the classification capability of neural networks. We also compare neural network capabilities with those of commonly used statistical methodologies. Experiments were designed and carried out on two-group classification problems to find answers to these questions. The prediction capability of the neural network models are better than traditional statistical models. The learning capability of the neural networks is improving compared to traditional models because the discriminate function is more complex. For real world classification problems, the usage of neural networks is highly recommended, for two reasons: learning capability and flexibility. Learning capability: Neural network classifies better in sterile experiments as performed in this research. Flexibility: Real life data are rarely not contaminated with noise, such as unknown distributions, and missing variables, etc. Neural networks differ from a statistical model that it is not dependent on any assumption concerning the data set distribution. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 699–717, 1997     

WEB系统中统计图绘制研究

简要介绍了GDI+,提出了在Web系统中利用GDI+实现统计图绘制的思路,并结合Visual C#.NET与Oracle数据库,举例阐述了统计图实现的关键技术和具体步骤,该技术在军队油库信息可视化研究与应用项目中得到很好应用。     

Optimal stopping in software testing

In this paper we address the problem of how to decide when to terminate the testing/modification process and to release the software during the development phase. We present a Bayesian decision theoretic approach by formulating the optimal release problem as a sequential decision problem. By using a non‐Gaussian Kalman filter type model, proposed by Chen and Singpurwalla (1994), to track software reliability, we are able to obtain tractable expressions for inference and determine a one‐stage look ahead stopping rule under reasonable conditions and a class of loss functions. © 2002 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

两栖装甲车辆车体随机应力统计

为探究某型两栖装甲车辆车体关键部位的疲劳失效原因,测取了不同路面工况下的载荷谱。采用雨流计数法对实测载荷谱进行计数,得到了相应载荷谱中应力循环的均值、幅值计数结果,利用数理统计的方法得到了各种路况的载荷分布模型,为疲劳分析提供了重要的数据并为海上试验及数据分析奠定了基础。雨流法及分布函数参数估计的程序实现,大大提高了随机应力谱的统计处理速度。     

一种北斗／CDMA导航系统数据融合的联邦卡尔曼滤波算法

北斗卫星与CDMA无线网络定位相结合的组合导航系统可以广泛应用于军事和民用领域,而有效进行数据融合是提高北斗/CDMA组合导航系统定位精度的关键.针对北斗/CDMA组合导航系统的特点,提出了一种基于联邦卡尔曼滤波的北斗/CDMA导航数据融合算法.算法采用机动目标的"当前"统计模型,分别建立了北斗定位系统和CDMA定位系统的状态方程,通过对相应定位参数进行滤波处理,提高了北斗/CDMA导航系统的定位精度.     

Technical note: Traffic intensity estimation

This note examines estimation of the traffic intensity in an M/G/1 queue. We show that the ratio of sample mean service times to the sample mean interarrival times has undesirable sampling properties. To remedy this, two alternative estimators are introduced. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

Performance and properties of Q‐Statistic monitoring schemes

In this article, we study the Shewhart chart of Q statistics proposed for the detection of process mean shifts in start‐up processes and short runs. Exact expressions for the run‐length distribution of this chart are derived and evaluated using an efficient computational procedure. The procedure can be considerably faster than using direct simulation. We extend our work to analyze the practice of requiring multiple signals from the chart before responding, a practice sometimes followed with Shewhart charts. The results show that waiting to receive multiple signals severely reduces the probability of quickly detecting shifts in certain cases, and therefore may be considered a risky practice. Operational guidelines for practitioners implementing the chart are discussed. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

内置谓词函数依赖及其推理规则

研究内置谓词函数依赖及其推理规则.首先提出内置谓词函数依赖,定义了内置谓词函数依赖的语法和语义;其次提出属性-约束集闭包概念,提出计算属性-约束集闭包的算法,判断内置谓词函数依赖逻辑蕴涵;然后提出内置谓词函数依赖的推理规则集A,证明推理规则集A是可靠且完备的,用于内置谓词函数依赖蕴涵分析的形式化证明;最后讨论了内置谓词函数依赖的应用.