Prediction of soft ground settlement based on BP neural network-grey system united model

PENG Tao; YANG An-ying; LIANG Xing; YUAN Qin

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Prediction of soft ground settlement based on BP neural network-grey system united model

更新时间：2026-06-25

- Prediction of soft ground settlement based on BP neural network-grey system united model
- Vol. 26, Issue 11, (2005)
- 作者机构：
  
  1. 中国地质大学环境学院,武汉,430074
  2. 深圳市规划与国土资源局土地投资开发中心,深圳,518034
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU433
- Online First：03 January 2014，
  
  Published：2005
- 稿件说明：
移动端阅览
PENG Tao, YANG An-ying, LIANG Xing, et al. Prediction of soft ground settlement based on BP neural network-grey system united model[J]. 2005, 26(11).
DOI：

PENG Tao, YANG An-ying, LIANG Xing, et al. Prediction of soft ground settlement based on BP neural network-grey system united model[J]. 2005, 26(11). DOI：

摘要

目前软基沉降预测多采用指数曲线和双曲线延伸法，其结果不够理想，神经网络在此方面的运用也存在一定的局限，虽然GM(1

1)模型在软基沉降预测领域已得到运用，但在已有的案例中所使用的等时距模型都没有明确说明所采用的插值方法。以深圳湾西部通道填海软基沉降预测分析为例，建立BP神经网络-灰色系统联合模型来探讨解决这一问题的方法。采用BP神经网络逼近非线性插值方法构建等时距时间序列数据，在此基础上建立沉降变形时间序列的GM模型，并建立相应的时间响应函数，预测沉降量。计算实例表明，该模型短期沉降预测结果比较准确，其最终沉降预测结果具有一定的工程参考价值。

Abstract

At present

people often predict soft-ground settlement with the method of exponential curve and double-curve extent; but the result is not ideal. The application of neural network to that exists some limitations. GM(1

1) model has been applied to this field

but all the equal-time settlement data model do not explain definitely interpolation method in existed case. The paper takes the predicting the soft ground settlement of Xibu tunnel filling sea project in Shenzhen for example

discusses the way to solve the problem through building the BP neural network-grey system united model; constructing the equal-time settlement time series data by BP neural network nonlinear interpolation method

on the basis of it

building the time series GM model for settlement

and building the time function to predict the settlement. The case study shows that the model is quite accurate in short-term settlement prediction

its long-term settlement prediction also has some project referential value.

关键词

Keywords

references

Views

1809

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Application of grey theory to data processing of fast load test

A multivariable grey model based on background value optimization and its application to subgrade settlement prediction

Settlement prediction of soft ground by modified layerwise summation method based on piezocone tests

Research on mesomechanical parameters of rock and soil mass based on BP neural network

Physical-mechanical properties and durability analysis of foamed lightweight soil based on excavated soil and fly ash

Related Author

YAN Yan

ZHANG Ming-yi

WANG Jia-tao

ZUO Yu-long

ZHU He-hua

LI Xiao-jun

LIU Han-bing

XIANG Yi-ming

Related Institution

Shandong Water Polytechnic College

Department of Civil Engineering, Qingdao Technology University

Department of Hydraulic and Hydropower Engineering, Tsinghua University

Department of Geotechnical Engineering, School of Civil Engineering, Tongji University

Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education, Tongji University

AI问答

⁰