研究了消息传播算法，根据贝叶斯网络的逆向推理给出了事故原因推理的贝叶斯网络结构；
This paper has researched information transform algorithm, and presented the Bayesian network structure of accident reason inference according to reversion inference.
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.
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.
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.
该文介绍了贝叶斯网络推理算法，分析了态势估计问题的本质特征和推理模式。
This paper introduces inference algorithm of Bayesian network and analyzes intrinsic characteristic and reasoning mode of situation assessment.
实验说明，基于贝叶斯网络推理的知识可以不断修正先验知识，获得对客户流失等问题的正确认识。
Experiments prove that the priority knowledge can be corrected continually by inference information of Bayesian network, and help to solve the problem of subscriber churn.
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.
同时利用贝叶斯网络实现概率推理，便于描述故障特征的变化及对变压器故障原因的快速分析。
At the same time, probability reasoning can be realized by BN, which can be used to describe changes of fault symptoms and analyze fault reasons of transformer.
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.
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.
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。
For dealing with the complexity and uncertainty in the target identification fusion, the fusion model of Bayesian Networks is used.
本文主要涉及的不确定推理模型包括主观贝叶斯的概率推理模型，可信度理论推理模型，证据理论及其改进推理模型以及神经网络推理模型。
In the paper, the models of uncertain reasoning are focused, such as the reasoning model of Bayes probability, Reliability theory, D-S evidence theory and Neural Network.
在控制系统中，将贝叶斯概率引入到模糊rbf神经网络中，增强了系统的推理能力，提高了飞机各个航道位置的模拟伺服精度。
In the control system, Bayes probability is introduced in the fuzzy RBF neural network and it intensity the inference ability and increase the servo precision.
因果推理是态势评估中的一个重要环节，用贝叶斯网络找出态势假设和事件之间的潜在关系，正是态势评估所需完成的功能。
Finding out the hidden patterns between situation hypothesis and events is the function needed in situation assessment. In this paper, a Bayesian network model for situation assessment is set up.
如何应用贝叶斯网络解决这一类混合不确定性的知识推理问题已成为研究热点。
How to use Bayesian network to solve this kind of mixed uncertainty knowledge inference has become a research hotspot.
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。
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。
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.
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