BP network train sample mode analyse the income by finite element model.

BP网络训练样本由有限元模型模态分析所得.

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So the reduced training set affects neither the edge training data nor the performance of FSVMs.

因此,减少训练样本既不影响边缘数据,也不影响FSVMs的性能.

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Modeling with this method can achieve high precision if the training samples are reliable.

只要训练样本可靠,采用该方法建模可以达到比较高的精度要求.

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The target model is used to search class characters based on analysis of training data.

目标模型是通过对训练样本数据的分析找到反映各类别的特征.

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The generalization ability of the networks relies on the pattern characters and the structure the network.

网络的泛化能力依赖于训练样本特性和网络结构,因此本文从这两方面来研究提高泛化能力的方法.

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In this paper , we discuss a new method for rule extraction based on hyper - box representation.

提出一种从训练样本提取基于超盒表示的模糊规则的方法,用于模式分类.

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