基于BP神经网络的横向受荷桩承载力预测  

Prediction of bearing capacity of lateral loading pile based on BP neural network

作　　者：蒋建平[1] JIANG Jian-ping(College of Ocean Science and Engineering, Shanghai Maritime University, Shanghai 201306, China)

机构地区：[1]上海海事大学海洋科学与工程学院,上海201306

出　　处：《水运工程》2017年第1期158-163,共6页Port & Waterway Engineering

基　　金：国家自然科学基金面上项目(41372319);上海市教委科研创新项目(14YZ101);上海市研究生教育创新计划实施项目(水利工程博士点培育)(20131129)

摘　　要：为研究横向受荷桩的承载性状,基于BP神经网络对其承载力进行预测。选取桩径、桩入土深度、荷载的偏心距、土的不排水抗剪强度作为神经网络的输入,得出黏土中横向受荷桩承载力的BP神经网络预测模型,发现训练BP神经网络时,桩承载力的拟合值与实测值的相对误差平均值为4.54%;检验BP神经网络时,桩承载力的预测值与实测值的相对误差平均值为5.39%。结果表明,建立的基于BP神经网络的黏土中横向受荷桩承载力预测模型是可行的。To investigate the bearing behaviors of lateral loading piles, we predict the ultimate bearing capacity of lateral loading pile based on BP neural network.Taking the pile diameter, depth of pile embedment, eccentricity of load, undrained shear strength of soil as the input of neural network, we obtain the prediction model of pile bearing capacity based on BP neural network.It is found that the average value of relative error of fitting value of pile bearing capacity compared with the observed value for 31 groups of independent variables training BP neural network model is 4. 5%; and the average value of relative error of prediction value of pile bearing capacity compared with the observed value for 7 groups of independent variables validating BP neural network model is 5.4%.The conclusion is drawn that the prediction model of bearing capacity of lateral loading pile based on BP neural network is feasible.

关 键 词：桩 承载力 横向荷载 BP神经网络 预测 误差 训练样本 检验样本 

分 类 号：TU473[建筑科学—结构工程] U65[建筑科学—土工工程]