结果，特殊的贝叶斯网络还可以处理因果关系和反事实关系。
Special versions of Bayesian networks, as it turned out, can manage causal and counterfactual relationships as well.
结果表明，基于MOR的贝叶斯网络分类模型可以有效地减小信用评估风险。
Results demonstrate that the Bayesian network classifiers based on MOR are able to reduce effectively the credit scoring risk.
本文数控机床故障诊断的贝叶斯网络模型的结构确立，以传统的故障树分析为基础。
On the basis of analyzing the advantages of Bayesian Networks when researching problems of uncertainty, a concrete model about the quality of workpiece of CNC lathe was established.
本文对极大或极小数据集下的贝叶斯网络学习进行了研究，并提出了相关的解决方案。
This thesis is about the study on learning Bayesian Network from extremely large or small datasets and its application.
为了分析匹配于进化种群的贝叶斯网络结构，给出了用于刻画局部贝叶斯网络度量的有关表示。
To analyze the structure of Bayesian networks to match the evolutionary population, this paper introduces some definitions of the local Bayesian network's metric.
对贝叶斯网络的参数学习进行了探讨，结合实例统计和相关性分析建立了车身偏差诊断的贝叶斯网络模型。
Parameter study of Bayesian network is investigated. According to the methods of example statistics and correlation analysis, Bayesian diagnosis model of body deviation is established.
针对舰船战场损伤评估的多元信息特点，建立了在观测操作条件下的舰船战场损伤评估的贝叶斯网络推理算法。
Object to the multi sensors character in warship battle damage assessment, a Bayesian net inference arithmetic is up forward considering observation operation.
贝叶斯网络是目前不确定知识和推理领域最有效的理论模型之一。
Bayesian network is one of the most efficient models in the uncertain knowledge and reasoning field.
贝叶斯网络以统计学为基础，是数据挖掘技术的一种方法。
On the base of statistics, the bayes network is a method of data mining.
特别是在当前数据较少或者较难获得的情况下，贝叶斯网络的这一优点更加明显。
Especially when the current data are scarce or hard to obtain, the advantage of the bayes network is evident.
贝叶斯网络是如今处理计算机系统，处理成千上万个变量和无数个观察的标准方法。
Bayesian networks are today's standard method for handling uncertainty in computer systems, processing thousands of variables and millions of observations.
贝叶斯网络用因果关系图的形式表达变量间相互关系，实现复杂系统的故障模式和效应分析。
Variable correlation is expressed with consequence graph in Bayesian Networks (BN), analysis of failure mode and effect of complex system is realized.
贝叶斯网络是数据采掘的一个非常有效的工具，它能够定性和定量地分析属性之间的依赖关系，进行概率推理。
Bayesian network as, a very useful tool in data mining, can provide qualitative and quantitative relationship between attributes and probability inference.
贝叶斯正则化方法提高BP神经网络的泛化能力。
Bayes' regularization raises the ability to extend of BP neural network.
贝叶斯网络是在不确定性环境下有效的知识表示方式和概率推理模型，是一种流行的图形决策化分析工具。
Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.
贝叶斯网络的学习。
论文提出了一种基于贝叶斯网络的软件项目风险分析过程。
A software project risk analysis process based on Bayesian networks is presented in this paper.
本文在分析了多种贝叶斯网络结构学习算法的基础上，并且根据水电仿真的应用背景，提出了一种根据多专家提供的规则库进行贝叶斯网络结构学习的新算法。
The Thesis analyses many kinds of Algorithm about Bayesian network structure learning, and then Setting-up a new Algorithm about structure learning Foundation on hydro-electrical simulation system.
提出了一种基于离散时间贝叶斯网络的动态故障树分析方法。
A new dynamic fault tree analysis method based on discrete-time Bayesian networks is proposed.
其次，分析了人工免疫系统和贝叶斯网络的基本原理。
Secondly, the paper analyses the basic principle AIS and Bayes network.
提出了一种基于贝叶斯网络的软件项目风险管理模型。
A software project risk management model based on Bayesian networks is presented.
针对多态系统故障树分析的难点，通过一个多态雷达系统的实例给出了一种基于贝叶斯网络的多态故障树分析方法。
Due to the difficulty of multi-state fault tree analysis, a new method based on Bayesian networks is proposed by means of an example of multi-state radar system.
研究了贝叶斯网络的学习问题，包括贝叶斯网络结构学习和贝叶斯网络参数学习。
The learning of Bayesian Networks is studied, including structure learning of Bayesian Networks and parameter learning of Bayesian Networks.
提出了基于贝叶斯网络的变压器状态综合评估方法，建立了贝叶斯网络状态评估模型。
We propose the method for Bayesian network based transformer synthesized condition evaluation and devise the Bayesian network condition evaluation model.
在现实世界中，不完整数据是广泛存在的，如何从不完整数据中学习贝叶斯网络的参数和结构一个非常实用而有价值的问题。
In the real world, not exact data exist here and there, how to learn the parameters and structure of Bayesian Networks from data is of practical value greatly.
基于相空间重构的非线性预报思想，建立一个时滞的BP神经网络模型，采用贝叶斯正则化方法提高BP网络的泛化能力。
Based on nonlinear prediction ideas of reconstructing phase space, this paper presents a time delay BP neural network model, whose generalization is improved utilizing Bayes' regularization.
在网络节点之间存在安全依赖关系的前提下，提出了一个基于贝叶斯方法的网络攻击定位和追踪模型。
Under the assumption of security dependence relation among different network nodes, a Bayesian model is put forward for locating and tracing a network attack.
并且与图像分类中统计方法的经典算法贝叶斯分类方法做了比较，结果发现，神经网络分类方法的分类效果要优于贝叶斯方法。
Comparing with Bayes method-the classical algorithm, we conclude that the neural network is better than Bayes method. This paper gives all the procedures of SAR image classification.
并且与图像分类中统计方法的经典算法贝叶斯分类方法做了比较，结果发现，神经网络分类方法的分类效果要优于贝叶斯方法。
Comparing with Bayes method-the classical algorithm, we conclude that the neural network is better than Bayes method. This paper gives all the procedures of SAR image classification.
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