Forecasting model of safe thickness for roof of karst cave tunnel based on support vector machines

WANG Yong; QIAO Chun-sheng; SUN Cai-hong; LIU Kai-yun

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Forecasting model of safe thickness for roof of karst cave tunnel based on support vector machines

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- Forecasting model of safe thickness for roof of karst cave tunnel based on support vector machines
- Vol. 27, Issue 6期　刊出日, (2006)
- 作者机构：
  
  北京交通大学土木建筑工程学院,北京,100044
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU94
- Online First：14 November 2013，
  
  Published：2006
- 稿件说明：
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WANG Yong, QIAO Chun-sheng, SUN Cai-hong, et al. Forecasting model of safe thickness for roof of karst cave tunnel based on support vector machines[J]. 2006, 27(6期　刊出日).
DOI：

WANG Yong, QIAO Chun-sheng, SUN Cai-hong, et al. Forecasting model of safe thickness for roof of karst cave tunnel based on support vector machines[J]. 2006, 27(6期　刊出日). DOI：

摘要

以某岩溶隧道为背景，采用二维弹塑性有限元方法对隧道开挖进行数值模拟计算，分析了隧道底部溶洞顶板安全厚度的影响因素，用支持向量机方法得出了能综合体现各影响因素的溶洞顶板安全厚度预测模型，并和多元线性回归得到的预测模型进行对比。计算结果表明，支持向量机预测模型较之多元线性回归模型，不但具有方便快捷的优点，而且具有更高的预测精度。

Abstract

Taking some tunnel as the background. and by using FEM numerical simulation

the factors affecting the safe thickness of roof of karst cave are analysed; and forecasting model of safe thickness of roof is obtained by support vector machines (SVM) and stepwise regression analysis.The result of calculation indicates that

SVM forecasting model not only has the advantages of convenience and swiftness compared with the linear regression model

but also has higher precision of prediction.

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