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     

贝叶斯网络下考虑攻击企图的目标威胁评估

为解决舰艇编队的防空目标威胁评估问题,针对现有威胁评估方法中忽略目标攻击企图,且只进行静态评估而未考虑目标机动导致的运动参数变化对威胁评估的影响之不足,提出了利用目标攻击时所表现出来的特征参数进行攻击企图估计,并分析了影响机动目标威胁程度的相关参数和变量,以目标信息更新周期为不同时间片,建立了用于动态评估目标威胁度的离散模糊动态贝叶斯网络结构模型。为适应编队防空中火力通道多、目标批次多的特点,将一般威胁等级从3级划分扩展为5级划分。给出了网络中主要节点的状态转移概率表和条件概率表。通过对机动目标按照典型攻击航路的威胁度变化仿真表明,所建立的模型和采用的方法合理有效,能够较为准确地反映目标威胁,贴近实战。     

用于态势估计的贝叶斯网络方法

态势估计系统需要对大量的不确定性知识进行处理,不确定性知识表示和推理是态势估计中的研究热点.利用贝叶斯网络技术,可以实现对不确定性知识的处理.为此讨论了贝叶斯网络理论,详细分析了态势估计的功能模型,提出事件检测是态势估计的核心和起点,研究了用于态势估计的贝叶斯网络的构建方法.该方法充分考虑贝叶斯网络的几项基本要素,可以解决态势估计领域中贝叶斯网络的构建问题.贝叶斯网络技术在态势估计领域具有广阔的前景,将极大地推动态势估计系统的发展.     

指数寿命产品可靠性增长试验的Bayes分析

针对指数寿命产品的定时、定数截尾试验方案,推广了Mazzuchi-Soyer模型的应用范围。首先引入模型假设,以狄氏分布作为先验分布,综合利用产品研制的历史信息和专家信息,结合产品研制各阶段试验数据,给出了各阶段可靠性的联合后验分布。然后利用Gibbs抽样算法解决后验推断计算问题,得到各阶段产品可靠性的Bayes点估计和区间估计。最后给出产品可靠性增长分析实例,表明了模型的优越性。     

Pairwise model discrimination with applications in lifetime distributions and degradation processes

Reliability data obtained from life tests and degradation tests have been extensively used for purposes such as estimating product reliability and predicting warranty costs. When there is more than one candidate model, an important task is to discriminate between the models. In the literature, the model discrimination was often treated as a hypothesis test and a pairwise model discrimination procedure was carried out. Because the null distribution of the test statistic is unavailable in most cases, the large sample approximation and the bootstrap were frequently used to find the acceptance region of the test. Although these two methods are asymptotically accurate, their performance in terms of size and power is not satisfactory in small sample size. To enhance the small‐sample performance, we propose a new method to approximate the null distribution, which builds on the idea of generalized pivots. Conventionally, the generalized pivots were often used for interval estimation of a certain parameter or function of parameters in presence of nuisance parameters. In this study, we further extend the idea of generalized pivots to find the acceptance region of the model discrimination test. Through extensive simulations, we show that the proposed method performs better than the existing methods in discriminating between two lifetime distributions or two degradation models over a wide range of sample sizes. Two real examples are used to illustrate the proposed methods.     

指数型产品可靠性验收试验的一种贝叶斯方法

采用贝叶斯方法 ,利用大量的历史数据和工程技术人员的丰富经验确定先验分布 ,制定出验收试验的一种新方案 .按照这一方案 ,在确保产品质量的前提下 ,可大大节省试验时间 ,从而得到十分可观的经济效益 .     

基于采样的非线性滤波方法

在系统阐述贝叶斯估计理论的基础上,分析和总结了扩展卡尔曼滤波、Sigma点卡尔曼滤波以及粒子滤波等方法的特点、使用条件以及局限性.介绍了扩展卡尔曼滤波方法并指出其缺陷;介绍了无轨迹卡尔曼滤波、中心差分卡尔曼滤波等确定性采样方法,并在加权统计线性回归意义下将其归结为Sigma点卡尔曼滤波方法;介绍了随机采样方法-粒子滤波方法,并指出其主要的研究方向.最后,对非线性滤波的发展趋势进行了展望.     

量化目标威胁等级的改进

目标威胁等级评判是战场数据融合中决策系统进行系统资源分配或重分配的基础。建立了基于模糊理论的目标威胁等级评判函数,提出了利用层次分析法(AHP)确定目标威胁等级加权向量的方法,实现了对目标威胁等级的量化评判。     

Network reliability assessment in a random environment

In this paper we consider networks that consist of components operating under a randomly changing common environment. Our work is motivated by power system networks that are subject to fluctuating weather conditions over time that affect the performance of the network. We develop a general setup for any network that is subject to such environment and present results for network reliability assessment under two repair scenarios. We also present Bayesian analysis of network failure data and illustrate how reliability predictions can be obtained for the network. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 574–591, 2003     

基于贝叶斯网络的船舶动力装置战场损伤分析

针对船舶动力装置战场损伤特点,对其损伤分析进行了研究,提出了基于贝叶斯网络的动力装置战场损伤模型.以主机振动为例,分析了模型的建立、更新和完善等.分析结果表明,该模型和方法提高了船舶动力装置的战场损伤分析的速度和准确性.