基于BP神经网络算法的顶管下穿地表沉降预测研究
Research on Prediction of Settlement of Pipe Jacking Through Surface Based on BP Neural Network Algorithm
李永杰1
作者信息
摘要
顶管下穿是一种常见的地下工程施工方法,然而,地下工程施工过程中的地层变形对工程安全和施工质量有着重要影响.为了有效预测顶管下穿地层变形,文章基于BP神经网络算法提出了一种预测方法.通过采集和整理在顶管下穿过程中的大量监测数据,并结合BP神经网络算法的训练和预测能力,建立了一个地层变形预测模型.通过实际案例验证,结果表明该方法能够高效准确地预测顶管下穿地层变形,为地下工程施工提供了可靠的参考依据.
Abstract
Pipe jacking undercrossing is a common construction method for underground engineering.However,ground deformation during the construction process of underground engineering has a significant impact on the safety and quality of the project.In order to effectively predict deformation of pipe jacking down through the formation,this paper proposes a prediction method based on the BP neural network algorithm.By collecting and organizing a large amount of monitoring data during the undercrossing process of pipe jacking,and combining the training and prediction capabilities of the BP neural network algorithm,a ground deformation prediction model is established.Through practical case verification,the results show that this method can efficiently and accurately predict deformation of pipe jacking through the formation,providing a reliable reference for underground engineering construction.
关键词
顶管下穿/地层变形/BP神经网络算法/预测方法Key words
pipe jacking undercrossing/ground deformation/BP neural network algorithm/prediction method引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据