The learning of Bayesian Networks.
贝叶斯网络的学习。
A software project risk management model based on Bayesian networks is presented.
提出了一种基于贝叶斯网络的软件项目风险管理模型。
This paper introduces a human gait recognition method based on Bayesian networks.
本文提出了一种基于贝叶斯网络的步态识别方法。
So application of Bayesian Networks for reasoning and diagnosis has a definite pertinence.
因此采用贝叶斯网络推理和诊断具有一定的针对性。
In the last, we give an example of dynamical Bayesian networks for time series data analysis.
最后给出了用于时间序列分析的动态贝叶斯网络的实例。
A new dynamic fault tree analysis method based on discrete-time Bayesian networks is proposed.
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 software project risk analysis process based on Bayesian networks is presented in this paper.
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。
During the process of Bayesian networks modeling, K2 and MCMC algorithms are utilized together.
在贝叶斯网络构造过程中，结合采用K2和MC - MC算法构建网络。
There are mathematical similarities connecting regression, neural networks and bayesian networks.
有数学的相似性连接的回归，神经网络和贝叶斯网络。
This approach is superior to the apparently "complex" methods such as Bayesian networks or neural networks.
这种方式倾向于 “复杂的”方法，比如Bayesian网络或神经网络。
Bayesian statistics theory: Expatiate the mathematic principle of Bayesian Networks, Bayesian statistics.
贝叶斯统计理论：阐述贝叶斯网络的数学原理——贝叶斯统计。
Beginning with the analysis of the Uncertainty in hypermedia system, the paper introduces the Bayesian networks.
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。
Special versions of Bayesian networks, as it turned out, can manage causal and counterfactual relationships as well.
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。
For dealing with the complexity and uncertainty in the target identification fusion, the fusion model of Bayesian Networks is used.
针对目标综合识别过程中的复杂性和不确定性特点，利用贝叶斯网络融合模型对融合识别过程进行概率建模及推理。
The paper presents a Bayesian networks(BN) framework for the reliability analysis of phased-mission systems(PMS), named PMS-BN model.
针对多阶段系统（PMS）的可靠性评估问题，提出了一种基于贝叶斯网络（BN）的可靠性分析模型PMS-BN。
The learning of Bayesian Networks is studied, including structure learning of Bayesian Networks and parameter learning of Bayesian Networks.
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。
A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in a small set of samples.
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。
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。
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 are today's standard method for handling uncertainty in computer systems, processing thousands of variables and millions of observations.
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。
The validity, faults diagnostic rate and faults isolated rate of the model must be evaluated all before Bayesian Networks model is used for faults diagnosis.
贝叶斯网络模型应用到故障诊断之前，必需对模型的正确性、故障诊断率、故障隔离率等进行全面的分析评估。
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.
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。
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.
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。
LIU Siyuan. On Information Fusion and Bayesian Networks Integrated Fault Diagnosis Theoretical Method and Experiments [d]. Qinhuangdao: Yanshan University, 2010.
[10]刘思远。信息融合和贝叶斯网络集成的故障诊断理论方法及实验研究[D]。秦皇岛：燕山大学，2010。
To analyze the structure of Bayesian networks to match the evolutionary population, this paper introduces some definitions of the local Bayesian network's metric.
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。
Firstly, the fundamentals of Bayesian networks are summarized. Then algorithm and data structure are described in detail. Finally, the implementation process is given.
首先我们总结了贝叶斯网络的基础，然后详细地描述了算法和数据结构，最后给出了具体实现过程。
By the inference mechanism based on Bayesian Networks, a modeling process of fault diagnosis system of AUV and the optimizing method of fault diagnosis strategy are given.
并通过基于贝叶斯网络的推理机制，给出了智能水下机器人故障诊断系统的建模过程以及对诊断策略的优化方案。
Techniques such as Bayesian networks or neural networks use highly expressive models, which try to produce a non-biased classifier in order to "describe" a corpus of documents.
Bayesian网络或神经网络等技术使用表达能力非常强的模型，力求生成无偏向的分类器来“描述”文档集。
Techniques such as Bayesian networks or neural networks use highly expressive models, which try to produce a non-biased classifier in order to "describe" a corpus of documents.
Bayesian网络或神经网络等技术使用表达能力非常强的模型，力求生成无偏向的分类器来“描述”文档集。
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