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Deformation Prediction of a Deep Foundation Pit Based on the Combination Model of Wavelet Transform and Gray BP Neural Network

机译:基于小波变换与Gray BP神经网络组合模型的深基坑变形预测

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摘要

The purpose of this study was to predict the deformation of a deep foundation pit based on a combination model of wavelet transform and gray BP neural network. Using a case of a deep foundation pit, a combination model of wavelet transform and gray BP neural network was used to predict the deformation of the deep foundation pit. The results show that compared with the traditional gray BP neural network model, the relative error of the combination model of wavelet transform and gray BP neural network was reduced by 2.38. This verified that the combined model has high accuracy and reliability in the prediction of foundation pit deformation and also conforms to the actual situation of the project. The research results can provide a valuable reference for foundation pit deformation monitoring.
机译:本研究基于小波变换和灰色BP神经网络的组合模型,对深基坑的变形进行预测。以某深基坑为例,采用小波变换和灰BP神经网络相结合的模型对深基坑变形进行预测。结果表明,与传统的灰色BP神经网络模型相比,小波变换与灰色BP神经网络组合模型的相对误差降低了2.38%;验证了组合模型在基坑变形预测方面具有较高的准确性和可靠性,也符合工程实际情况。研究结果可为基坑变形监测提供有价值的参考。

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