Secondly, the paper analyses the basic principle AIS and Bayes network.
其次，分析了人工免疫系统和贝叶斯网络的基本原理。
On the base of statistics, the bayes network is a method of data mining.
贝叶斯网络以统计学为基础，是数据挖掘技术的一种方法。
Especially when the current data are scarce or hard to obtain, the advantage of the bayes network is evident.
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。
Bayes' regularization raises the ability to extend of BP neural network.
贝叶斯正则化方法提高BP神经网络的泛化能力。
This paper establishes dynamic forward feedback correction model with the method of combining Bayes regularization and BP neural network.
文中采用贝叶斯正则化与BP网络结合的方法，建立动态前馈校正模型。
Comparing with Bayes method-the classical algorithm, we conclude that the neural network is better than Bayes method. This paper gives all the procedures of SAR image classification.
并且与图像分类中统计方法的经典算法贝叶斯分类方法做了比较，结果发现，神经网络分类方法的分类效果要优于贝叶斯方法。
Based on nonlinear prediction ideas of reconstructing phase space, this paper presents a time delay BP neural network model, whose generalization is improved utilizing Bayes' regularization.
基于相空间重构的非线性预报思想，建立一个时滞的BP神经网络模型，采用贝叶斯正则化方法提高BP网络的泛化能力。
The paper used the Bayes regularization algorithm to train the BP network, the precision and generalization of which are better than the network that uses ordinary training algorithms.
本文采用贝叶斯规则化的训练方法，训练好的BP网络较常用的训练方法具有更好的精度和泛化能力。
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.
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。
The results show that the results predicted by Bayes model are both in good agreement with the practical conditions and the results obtained from the neural network model and fuzzy probability model.
研究结果表明，该模型判别预测结果与人工神经网络模型及模糊概率模型的判别结果及实际岩爆情况较吻合。
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.
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.
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。
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