条件概率关系数据库模型

现实世界中大量存在着的不确定性信息，关系数据库模型仅视它们为空值，有必要增强其处理这类信息的能力，文章在总结前人工作的基础上推广关系数据库模型，创建有效处理随机型不确定性信息的条件概念关系数据库模型，该模型通过在关系模式中增加一个条件概率测度属性，为每条记录指定适当的条件概率的途径，来表示不确定性信息。文中以对象码为基本工具，创建了条件概率关系结构；以特征函数为基本工具，定义了一套基于该结构的代数运算规则。条件概率的语意比概率的语意广泛，灵活，因而该模型能有效克服概率关系模型的许多不足。     

Markov analysis of qualitative dynamics1

Common sense sometimes predicts events to be likely or unlikely rather than merely possible. We extend methods of qualitative reasoning to predict the relative likelihoods of possible qualitative behaviors by viewing the dynamics of a system as a Markov chain over its transition graph. This involves adding qualitative or quantitative estimates of transition probabilities to each of the transitions and applying the standard theory of Markov chains to distinguish persistent states from transient states and to calculate recurrence times, settling times, and probabilities for ending up in each state. Much of the analysis depends solely on qualitative estimates of transition probabilities, which follow directly from theoretical considerations and which lead to qualitative predictions about entire classes of systems. Quantitative estimates for specific systems are derived empirically and lead to qualitative and quantitative conclusions, most of which are insensitive to small perturbations in the estimated transition probabilities. The algorithms are straightforward and efficient.     

Inference and learning in hybrid probabilistic network

This paper proposed a novel hybrid probabilistic network, which is a good tradeoff between the model complexity and learnability in practice. It relaxes the conditional independence assumptions of Naive Bayes while still permitting efficient inference and learning. Experimental studies on a set of natural domains prove its clear advantages with respect to the generalization ability.     

Probabilistic analysis of uncertainties in seismic hazard assessment

Sources and current methods of analysis of uncertainty from randomness, fuzziness and ignorance or incomplete knowledge in seismic hazard assessment problem are briefly discussed at beginning; understandings of the authors are then presented in the following order. All three types of uncertainty come from incomplete knowledge. Probabilistic method can be applied to all of them, objective probability for random factors and subjective probability for the other two types of uncertain factors. Discrete subjective probability mass functions for incomplete and fuzzy factors can be obtained from logic-tree and membership functions respectively. Fractile curves may be used to show the scattering of any uncertainty factor, but a unified probabilistic treatment may be applied to any combination of all three types of uncertainty.     

基于邻域统计特性的概率神经网络及其在自动目标识别中的应用

在概率神经的一种改进模型－ＦＤＯ网络的基础上，提出在设计网络收敛域时进一步考虑每一像素点周围８邻域的影响，对网络的作用函数加以修，使改进后的网络具有稳定性好且收敛速度快的优点。通过实验对改进前后网络的识别性能加以比较，证明改进后的网络特别适用于噪声图像的识别。     

后桥壳的可靠性优化设计

该文讨论了后桥壳的可靠性优化设计问题.在基本随机变量的概率特性已知的情况下,应用随机摄动法和约束随机方向法对后桥壳进行可靠性优化设计,并编制了实用的计算机程序,可以迅速准确地得到后桥壳的可靠性设计参数.     

P油田长4+52小层孔隙度三维模型的建立

为了更准确的评价P油田主要产层长4 52小层的储集能力，以随机模拟建模方法对该层的孔隙度进行研究，建立孔隙度分布三维模型。研究表明，长4 52小层属于低孔储层，平均孔隙度为11．85％。根据P油田储层物性分类原则，该储层在本区分布较为广泛，是今后挖潜的重点。     

Structural reliability optimization using an efficient safety index calculation procedure

The objective of this paper is to conduct reliability-based structural optimization in a multidisciplinary environment. An efficient reliability analysis is developed by expanding the limit functions in terms of intermediate design variables. The design constraints are approximated using multivariate splines in searching for the optimum. The reduction in computational cost realized in safety index calculation and optimization are demonstrated through several structural problems. This paper presents safety index computation, analytical sensitivity analysis of reliability constraints and optimization using truss, frame and plate examples.