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邓子胜. 基于径向基神经网络的深基坑非线性位移反分析[J]. 岩土工程学报, 2005, 27(5): 554-557.
引用本文: 邓子胜. 基于径向基神经网络的深基坑非线性位移反分析[J]. 岩土工程学报, 2005, 27(5): 554-557.
DENG Zisheng. Nonlinear displacement back-analysis for deep excavation based on radial basis neural network[J]. Chinese Journal of Geotechnical Engineering, 2005, 27(5): 554-557.
Citation: DENG Zisheng. Nonlinear displacement back-analysis for deep excavation based on radial basis neural network[J]. Chinese Journal of Geotechnical Engineering, 2005, 27(5): 554-557.

基于径向基神经网络的深基坑非线性位移反分析

Nonlinear displacement back-analysis for deep excavation based on radial basis neural network

  • 摘要: 以支护结构-土非线性共同作用的土压力计算模型为基础,提出了非线性共同作用弹性地基反力法;然后将径向基神经网络引入深基坑位移反分析,研究了根据深基坑空间效应的表现形式及规律选取适当剖面进行位移反分析的原理与方法,编制了计算程序。它可以逐工况地对支护结构不同标高和平面位置处的实测位移进行反分析,从而使反演的土性参数包含了时空效应和非线性共同作用的影响。工程算例表明:围护墙位移的反演计算结果与实测值吻合良好。

     

    Abstract: Based on the new earth pressure computation model the elastic subgrade reaction method was put forward to consider the nonlinear interaction between the supporting structure and soil. Then the radial basis neural network was introduced into the displacement back-analysis for deep excavation, the principle and methods of the displacement back-analysis for the sections chosen according to the behaviorl and spatial effect of excavation were studied, and the computer program was developed, which can be used to back-analyze the measured displacements at some places of the supporting structure in different construction stages. So the soil parameters gained by back-analysis embody the influence of the space-time effects and nonlinear interaction. The results of the practical application of this program to an engieering project show that the calculated and measured displacements of retaining wall agree with each other very well.

     

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