贝叶斯网络的学习。
数控车床；智能故障诊断；贝叶斯网络；振动分析。
CNC lathe; intelligent fault-diagnosis; Bayesian Network; vibration analysis.
因此采用贝叶斯网络推理和诊断具有一定的针对性。
So application of Bayesian Networks for reasoning and diagnosis has a definite pertinence.
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.
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.
最后给出了用于时间序列分析的动态贝叶斯网络的实例。
In the last, we give an example of dynamical Bayesian networks for time series data analysis.
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.
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.
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.
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.
研究了基于贝叶斯网络的推理模型以及基于此模型的推理算法。
The inference model based on Bayesian Network is discussed and the algorithm based on the model is presented.
贝叶斯统计理论：阐述贝叶斯网络的数学原理——贝叶斯统计。
Bayesian statistics theory: Expatiate the mathematic principle of Bayesian Networks, Bayesian statistics.
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.
该文提出了将贝叶斯网络应用于高压直流系统可靠性评估的方法。
A method of reliability evaluation for HVDC systems based on Bayesian network is proposed in this paper.
本文通过分析超媒体系统中的不确定性因素，引入了贝叶斯网络方法。
Beginning with the analysis of the Uncertainty in hypermedia system, the paper introduces the Bayesian networks.
提出一种在小样本的情况下，基于多层贝叶斯网络的医学图像语义建模方法。
A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in a small set of samples.
根据威胁识别与贝叶斯网络的特点，提出了基于贝叶斯网络的威胁识别方法。
According to characteristics of threat identification and Bayesian network, a method of threat identification based on Bayesian network is brought forward.
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.
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.
介绍了贝叶斯网络的概念，给出一个实例，分析了贝叶斯网络推理的方法和过程。
This thesis gives a introduction to the concept of Bayesian networks, and gives one example, the method and process is presented to Bayesian networks inference.
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.
针对油藏分布预测的问题，提出了一个贝叶斯网络融合模型并设计了相应的算法。
Bayesian fusion model is put foreword with a corresponding algorithm designed to forecast the oil reservoir distribution.
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.
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.
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.
有环贝叶斯网络的研究，为管理软件项目迭代过程风险提供了建模方法和模型求解算法。
Cyclic Bayesian network provides modeling method and inference algorithms for the management of software project iterative process risk.
以特征信息结构树为基础，对贝叶斯网络模型进行推理，来获得客户需求的兴趣集中点。
Through reasoning Bayesian network model based on the features information construction tree of client requirement, the client requirement concentration is acquired.
结合贝叶斯网络和神经网络，提出了一种建立数据驱动型的动态线性回归系统模型的方法。
A new method was represented to model dynamic linear regression system driven by data, in which a bayesian network was combined with the RBF neural network.
根据动态联盟企业信息具有不确定性的特点，应用贝叶斯网络对企业的风险概率进行识别。
According to the uncertain characteristics of information in virtual enterprise, the Bayesian network is used to identify its risk probability.
该方法可避免现有的贝叶斯网络学习过于依赖数据、对数据的数量和质量要求过高等问题。
This method can avoid the problems of depending on a large number of data with high quality in existing Bayesian network learning.
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