多步滚动实时预报法在深基坑开挖监测中的应用研究

STUDY ON APPLICATION OF MULTI-STEP SCROLL REAL-TIME PREDICTION METHOD TO MONITORING OF DEEP FOUNDATION PIT EXCAVATION

对传统BP神经网络存在的不足进行改进,并将其应用于深基坑开挖监测中,建立深基坑变形的实时预报模型;提出一种基于时间效应的多步滚动实时预报法,并利用Windows系统平台,在MATLAB7.0环境下,采用可视化的面向对象编程技术,编制深基坑变形实时预报的计算机程序。实例分析表明:该方法收敛速度快,预测精度高,预报值与实测值吻合较好,深基坑变形的实时预报具有一定的实用性。

Improved back-propagation(BP) neural network is used to predict the deformation of deep foundation pit.A real-time predication model is established for deformation of deep foundation pit;and an effective predicting method called multi-step scroll real-time prediction method based on time effect is put forward.Making use of the Windows system platform,under the environment of MATLAB 7.0,adopting visual object-oriented programming technique,the real-time prediction program of the deep foundation pit deformation is developed.The result indicates that the model proposed here has fast approximation and high precision;and the predicted values agree well with the measured ones.The proposed method is a useful tool for deformation prediction of deep foundation pit.