| 基于SVM的溶洞顶板安全厚度智能预测模型 |
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| 引用本文： | 王勇,乔春生,孙彩红,刘开云.基于SVM的溶洞顶板安全厚度智能预测模型[J].岩土力学,2006,27(6):1000-1004. |
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| 作者姓名： | 王勇 乔春生 孙彩红 刘开云 |
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| 作者单位： | 北京交通大学 土木建筑工程学院，北京 100044 |
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| 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。
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| 关 键 词： | 岩溶隧道 有限元 安全厚度 支持向量机 预测模型 |
| 文章编号： | 1000-7598-（2006）06-1000-05 |
| 收稿时间： | 2004-09-15 |
| 修稿时间： | 2004-09-15 |
Forecasting model of safe thickness for roof of karst cave tunnel based on support vector machines |
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| WANG Yong,QIAO Chun-sheng,SUN Cai-hong,LIU Kai-yun.Forecasting model of safe thickness for roof of karst cave tunnel based on support vector machines[J].Rock and Soil Mechanics,2006,27(6):1000-1004. |
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| Authors: | WANG Yong QIAO Chun-sheng SUN Cai-hong LIU Kai-yun |
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| Institution: | College of Civil and Architecture Engineering, Beijing Jiaotong University, Beijing 100044, China |
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| 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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| Keywords: | karst tunnel FEM safe thickness support vector machines(SVM) forecasting model |
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