Bayes linear analysis for graphical models: The geometric approach to local computation and interpretive graphics

This paper concerns the geometric treatment of graphical models using Bayes linear methods. We introduce Bayes linear separation as a second order generalised conditional independence relation, and Bayes linear graphical models are constructed using this property. A system of interpretive and diagnostic shadings are given, which summarise the analysis over the associated moral graph. Principles of local computation are outlined for the graphical models, and an algorithm for implementing such computation over the junction tree is described. The approach is illustrated with two examples. The first concerns sales forecasting using a multivariate dynamic linear model. The second concerns inference for the error variance matrices of the model for sales, and illustrates the generality of our geometric approach by treating the matrices directly as random objects. The examples are implemented using a freely available set of object-oriented programming tools for Bayes linear local computation and graphical diagnostic display.     

城市结合部交通现代化探讨

我国城市结合部交通比较落后,是许多城市交通的薄弱环节。为此,城市结合部交通现代化发展战略应为可持续发展;智能化、信息化发展;多种交通方式协调发展,并用模糊评价方法对其现代化水平进行定量评价。     

受内压圆柱筒体开孔-接管区应力集中的有限元分析

利用 ANSYS有限元分析软件通过三个算例对圆柱形筒体小开孔直接管区、大开孔直接管区、大开孔斜接管区的应力分布状况进行了研究 .从中了解到了最大第一主应力的变化规律 ,得出在弹性范围内的应力集中系数 ,并且得到ASME规范中的算式较好的验证     

An efficient algorithm for finding the M most probable configurationsin probabilistic expert systems

A probabilistic expert system provides a graphical representation of a joint probability distribution which enables local computations of probabilities. Dawid (1992) provided a flow- propagation algorithm for finding the most probable configuration of the joint distribution in such a system. This paper analyses that algorithm in detail, and shows how it can be combined with a clever partitioning scheme to formulate an efficient method for finding the M most probable configurations. The algorithm is a divide and conquer technique, that iteratively identifies the M most probable configurations.     

Nexus及其在英汉文学翻译中的应用

junction 和nexus 是丹麦语言学家Otto Jespersen 提出的一对语言学概念.Jespersen认为一个首品词(primary)和一个附着语(adjunct)组合成一个偏正结构(junction),而一个首品词(primary)和一个谓语(predicate)组合成一个主谓结构 (nexus).Junction 是一个意义的合成,只表达一个意义;Nexus则包含两个意义.Jespersen对比二者得出结论:junction 就好比一幅画,而nexus则是一个过程,一出戏;前者较为呆板,缺乏生气,后者却灵活生动,富于生机.本文着重比较了junction和nexus的不同之处,进而讨论了nexus在英汉文学翻译中的应用,以期在实践中验证nexus的优势.     

一种宽带正交模耦合器的设计

介绍了一种基于对称五端口分支形式的宽带正交模耦合器.对称五端口分支将方波导内的双极化波分离成为水平和垂直2个相互垂直的分量.其特点为:相对于公共波导对称放置的一对相同的波导双接头分配给每一主模,因此每个接头传输主模提供信号一半的能量,双接头的3 dB信号必须用附加的元件适当组合,以便在一个界面端口上提供给定极化总的信号能量.文中介绍的宽带正交模耦合器主要由对称五端口分支、功率合成器及相应的变换段组成.利用阻抗变换原理进行仿真计算,在理论分析的基础上进行了大量的实验研究.最后给出了正交模耦合器在X波段大于90%波导带宽工作的电性能测量结果.     

无定向测量附合导线网的数据处理

对工程测量中无定向导线网的平差原理、计算方法作了综合论述,提出了无定向附合导线点坐标求定公式及误差方程式,并对全网平差计算及精度评定进行了分析.建立了运用计算机进行数据处理的模块化功能结构,解决了无定向导线网的平差数据处理问题     

Identification of composite (∑+II) arma models by relatively simpler models

In the real world situations, many time series are aggregates of two or more time series. An aggregation may take place due to an addition or the product or both of two or more time series. We are often interested in the study of the properties of aggregates which are, in turn, dependent on the properties of the constituent series. Motivated by this problem, the authors study in this paper the properties of models generated by the operator (Σ+II) on autoregressive-moving-average (ARMA) processes of orders (p_i,q_i), i = l→n . A few practical examples where such models have been used are given in the introduction and an illustrative numerical example is discussed at the end of the paper.     

圆柱壳开孔补强结构的有限元分析

使用ANSYS软件计算同一筒径,不同开孔直径壳体,共六个模型的应力集中系数.按等面积补强法计算出以上模型分别采用补强圈补强和厚壁接管补强各自的厚度,建立相应的模型,求出应力集中系数.有限元的分析方法可以证明:在局部区域内产生较大的塑性变形时采用补强圈或厚壁接管补强,均可有效的改善孔边的应力集中,相同壳体直径,开相同大小的孔时,接管补强后的应力集中系数小于补强圈补强的应力集中系数.     

Applications of a general propagation algorithm for probabilistic expert systems

A probabilistic expert system provides a graphical representation of a joint probability distribution which can be used to simplify and localize calculations. Jensenet al. (1990) introduced a flow-propagation algorithm for calculating marginal and conditional distributions in such a system. This paper analyses that algorithm in detail, and shows how it can be modified to perform other tasks, including maximization of the joint density and simultaneous fast retraction of evidence entered on several variables.