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.
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 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。
The learning of Bayesian Networks is an important tache, which combines training data with prior knowledge and model evaluation to acquire the structure hidden in data and parameters.
贝叶斯网络的学习是数据挖掘中非常重要的一个环节，是将先验知识和模型评价融入训练数据，获得数据中隐藏的拓扑结构和参数的过程。
The learning of Bayesian Networks is an important tache, which combines training data with prior knowledge and model evaluation to acquire the structure hidden in data and parameters.
贝叶斯网络的学习是数据挖掘中非常重要的一个环节，是将先验知识和模型评价融入训练数据，获得数据中隐藏的拓扑结构和参数的过程。
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