基于神经网络模型的软基工后变形分析

Analysis of post-construction settlement of embankment on soft ground based on neural networks model

基于神经网络理论和反向传播算法,建立了软基工后变形预测分析人工神经网络模型,结合汕汾高速公路软基工后沉降实测数据,对模型进行学习训练,并利用神经网络模型进行工后变形预测,验证表明,预测值与实测值有较好的一致性,由于其能以较高的精度去逼近任意非线性函数,从而在软基变形分析上显示出较强的实用价值和优越性。

Based on the Neural Networks Theory and the Back Propagation Algorithm, the artificial neural networks model of post-eonstruction settlement of embankment on soft ground is presented. Applying the observational data based on field measurement into the neural networks model, the case studies show the accordance of the predicted settlements by the proposed model with the measured data.