基于BP神经网络算法的路基工后沉降预测分析

Prediction Analysis of Subgrade Settlement after Construction Based on Neural Network Algorithm

摘要: 路基工后沉降对道路的运营维护具有重要影响，基于BP神经网络算法的强大非线性映射能力，以时间为输入、沉降量为输出进行神经网络训练，建立沉降与时间的函数关系。工程案例分析表明采用BP神经网络算法进行路基工后沉降预测具有一定的精度，能够满足工程要求。

Abstract: Subgrade settlement after construction plays an important role in operation and maintenance of road. As powerful nonlinear mapping ability of BP neural network algorithm, time and settlement are taken as input and output of neural network algorithm, respectively. Function relationship between settlement and time is established after neural network training. The engineering case analysis shows that the BP neural network algorithm has a certain accuracy to predict the post construction settlement of the subgrade and can meet the engineering requirements.