Settlement prediction model of roadbed on soft ground based on artificial neural network with interference function

FAN Kun; YANG Tao; LI Guo-wei

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Settlement prediction model of roadbed on soft ground based on artificial neural network with interference function

更新时间：2026-06-25

- Settlement prediction model of roadbed on soft ground based on artificial neural network with interference function
- Vol. 25, Issue 2, (2004)
- 作者机构：
  
  1. 上海海运学院计算中心,上海,200135
  2. 上海理工大学城市建设与环境工程学院,上海,200093
  3. 河海大学岩土所,江苏,南京,210098
- 作者简介：
- 基金信息：
- DOI：
  CLC： TB115
- Online First：15 July 2014，
  
  Published：2004
- 稿件说明：
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FAN Kun, YANG Tao, LI Guo-wei. Settlement prediction model of roadbed on soft ground based on artificial neural network with interference function[J]. 2004, 25(2).
DOI：

FAN Kun, YANG Tao, LI Guo-wei. Settlement prediction model of roadbed on soft ground based on artificial neural network with interference function[J]. 2004, 25(2). DOI：

摘要

建立了基于函数干涉神经网络的公路软基沉降预测模型。工程实例表明，所建议的模型外延性好，而且，可以由较短预压期内沉降观测资料预测远期沉降发展，与传统沉降预测模型相比具有显著的优越性，工程应用前景广阔。

Abstract

Based on the measured settlements of road embankment on soft ground during preloading

a new settlement prediction model is established by the BP network with interference function. Its application to a practical case shows that the proposed model has good extensionality

and can be used to predict future settlements with higher precision by means of measured settlements during a short period of preloading. The proposed model can overcome the defaults of some cure fitting methods and the traditional BP model

and has widely applied foreground in expressway construction.

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