Taking cable tension indices as inputs of neural network for both training and testing, damage locations are indicated by the outputs of the network.
以不同损伤程度下斜拉索张力指标作为神经网络的训练与测试输入，由神经网络的输出来指示损伤位置。
Based on the powerful nonlinear reflection and training function of artificial neural networks, the model of BP neural network for foundation piles integrity testing is put forward.
利用人工神经网络强大的非线性映射能力和学习训练功能，提出了基于BP网络的基桩完整性检测模型。
The method uses wavelet transform and principle component analysis to preprocess fault signal, afterward training and testing wavelet neural network with the preprocessed fault characteristic data.
该方法首先利用小波变换和主成分分析对故障信号进行预处理，然后用处理后的故障特征数据对小波神经网络进行训练和测试。
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