基于BP神经网络的软土路基施工期沉降预测与仿真

英文篇名：Prediction and Simulation of Settlement of Highway Soft Foundation During Construction Based on BP Neural Network
中文刊名：山东交通学院学报
英文刊名：Journal of Shandong Jiaotong University
作者：刘鹏 ; 夏元友
英文作者：LIU Peng1 ; XIA Yuan-you2(1.Guangzhou Water Conservancy and Hydropower Investigation and Design Academy ; Guangzhou 510650 ; China ; )(2.Wuhan University of Technology ; Wuhan 430070 ; China)
中文关键词：软基沉降 ; BP神经网络 ; 预测 ; 仿真控制
英文关键词：settlement of soft foundation ; BP neural network ; prediction ; simulated control
出版日期：2008-09-15
机构：广州市水利水电勘测设计研究院;武汉理工大学;
年：2008
期：03
出版单位：山东交通学院学报

摘要

在高速公路软基沉降预测与施工控制中,把现场填土厚度、时间及实测沉降量信息作为学习样本,经过BP神经网络训练后,建立了动态仿真预测模型,用该模型预测当前及下一级填土后的沉降量,判断下一级填土是否可行及对路堤稳定性的影响,以实现对软基沉降及工程施工的事前仿真控制,避免工程事故的发生。实际工程应用表明,该模型的预测精度满足工程建设的需要。
In the prediction and control of settlement of highway soft foundation,taking the field measuring information of the thickness of roadbed construction,time,and settlements as studying samples,simulated prediction model which varies with time based on BP neural network is established.The model can predict the present and next roadbed construction settlement and thus can also predict whether the next roadbed construction is feasible or not and whether the stability of the roadbed is influential or not.The simulated control of settlement of soft foundation before roadbed construction has been done to avoid engineering accidents.Application in highway construction shows that the prediction accuracy of the model can meet the needs of engineering construction and the method is feasible.

引文

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