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。
After the theory and inference mechanism of Bayesian networks was introduced, this paper mainly studies the application of Bayesian networks in emitter's threat level assessment.
以贝叶斯网络及其推理机制为基础，主要研究了贝叶斯网络在辐射源威胁等级评估方面的应用。
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.
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。
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.
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。
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