基于LSSVM对盾构施工诱发地面塌陷变形预测

Abstract
Figure/Table
References (23)
Related Citation (15)

Download: PDF (689 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract When shield crossed the sandy cobble stratum in Chengdu metro No.1 and No.2 lines，the induced surface subsidence reached as high as dozens of times. Surface collapse deformation curve is influenced by many factors，and the influences of the factors on surface collapse deformation curve show the nonlinear characteristics. So the surface collapse deformation curve is difficult to solve with mathematical formulas. Least squares support vector is a machine learning method based on the statistical learning theory. It can avoid shortcomings of traditional neural network and analyze influencing rule on the result with complicated factors. Thereby least squares support vector machine method was introduced to establish prediction model for surface collapse deformation. Prediction model took physico-mechanical parameters of stratum，buried depth of shield and ground loss value as input parameters. Though testing sample data，the prediction mode has strong generalization ability，and its prediction result has high accuracy and reliability.

Key words： tunnelling engineering least square support vector machine surface collapse prediction for deformation curve statistical analysis

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	BAI Yongxue1
	QI Taiyue1
	LI Youdao2
	WU Zhanrui1

Cite this article:

BAI Yongxue1,QI Taiyue1,LI Youdao2, et al. PREDICTION FOR SURFACE COLLAPSE DEFORMATION OF SHIELD CONSTRUCTION BASED ON LSSVM[J]. , 2013, 32(s2): 3666-3674.

URL:

https://rockmech.whrsm.ac.cn/EN/Y2013/V32/Is2/3666

[1]	李希元，闫静雅，孙艳萍. 盾构隧道施工工程事故的原因与对策[J]. 地下空间与工程学报，2005，1(6)：965-971.(LI Xiyuan，YAN Jingya，SUNYanping. Reasons and countermeasures of accidents happenedduring the shield tunnel construction[J]. Chinese Journal of Underground Space and Engineering，2005，1(6)：965-971.(in Chinese))
[2]	马文涛. 基于灰色最小二乘支持向量机的边坡位移预测[J]. 岩土力学，2010，31(5)：1670-1674.(MA Wentao. Forecasting slope displacements based on grey least square support vector machines[J].Rock and Soil Mechanics，2010，31(5)：1670-1674.(in Chinese))
[3]	井彦林，仵彦卿，林杜军，等.基于最小二乘支持向量机的黄土湿陷性预测挖掘[J]. 岩土力学，2010，31(6)：1865-1870.(JING Yanlin，WU Yanqing，LIN Dujun，et al. Prediction of loess collapsibility by using data mining based on least squares support vector machines[J]. Rock and Soil Mechanics，2010，31(6)：1865- 1870.(in Chinese))
[4]	赵洪波，冯夏庭.支持向量机函数拟合在边坡稳定性估计中的应用[J].岩石力学与工程学报，2003，22(2)：241-245.(ZHAOHongbo，FENG Xiating. Application of support vector machine function fitting to slope stability evaluation[J].Chinese Journal of Rock Mechanics and Engineering，2003，22(2)：241-245.(in Chinese))
[5]	邬凯，盛谦，张勇慧，等. 基于最小二乘支持向量机的边坡稳定性预测[J]. 水力发电学报，2009，28(2)：66-71.(WUKai，SHENGQian，ZHANGYonghui，etal. Slope stability prediction based on least square support vector machines[J].Journal of Hydro Electric Engineering，2009，28(2)：66-71.(in Chinese))
[6]	罗战友，杨晓军，龚晓南.基于支持向量机的边坡稳定性预测模型[J].岩石力学与工程学报，2005，24(1)：144-148.(LUO Zhanyou，YANG Xiaojun，GONG Xiaonan. Support vector machine model in slope stability evaluation[J]. Chinese Journal of RockMechanics and Engineering，2005，24(1)：144-148.(in Chinese))
[7]	田景文，高美娟. 人工神经网络算法研究及应用[M]. 北京：北京理工大学出版社，2006：227-235.(TIAN Jingwen，GAO Meijuan. Study and utilization on algorithm of artificial neural net[M]. Beijing：Beijing Institute of Technology，2006：227-235.(in Chinese))
[8]	VAPNIK V. The nature of statistical learning theory[M]. New York：Springer-Verlag，1999：1-10.
[9]	VAPNIK V. An overview of statistical learning theory[J]. IEEE Transaction on Neural Networks，1999，10(5)：988-999.
[10]	CORTES C，VAPNIC V.Support vector networks[J].Machine Learning，1995，20(1)：1-25.
[11]	SUYKENS J A K，VANDEWALLE J. Least squares s-upport vector machine classifiers[J]. Neural Net-work Letters，1999，9(3)：293-300.
[12]	SUYKENS J A K，VANDEWALLE J. Recurrent least squares support vector machines[J]. IEEE Transactions on Circuits and Systems，2000，47(7)：1109-1114.
[13]	SUYKENS J A K．Support vector machines：a nonlinear modeling and control perspective[J]. European Journal of Control，2001，7(2/3)：311-327.
[14]	CHERKASSKY V，MA Y Q. Practical selection of SVM parameters and noise estimationfor SVM regression[J]. Neural Networks，2004，17(1)：113-126.
[15]	王明年，魏龙海，刘大刚. 卵石地层中地下铁道施工力学的颗粒离散元法模拟技术及应用[M]. 成都：西南交通大学出版社，2010：1-8.(WANG Mingnian，WEI Hailong，LIU Dagang. Applicationand simulation of granulardiscrete element method on the mechanical behaviorof subway construction in cobble stratum[M]. Chengdu：Southwest Jiaotong UniversityPress，2010：1-8.(in Chinese))
[16]	KARIM A M. Three-dimensional discreteelement modeling of tunneling in sand[Ph. D. Thesis][D].Edmonton，Alberta：University of Alberta，2007.
[17]	刘建航，侯学渊.盾构法隧道[M].北京：中国铁道出版社，1991：329-335.(LIU Jianhang，HOU Xueyuan. Methodofshield tunneling[M].Beijing：China Railway Publishing House，1991：329-335.(in Chinese))
[18]	柳厚祥. 地铁隧道盾构施工诱发地层移动机制分析与控制研究[博士学位论文][D].西安：西安理工大学，2008.(LIU Houxiang. Themechanismanalysisandcontrolofgroundmovementsinduced bysubwayshieldtunnelingconstruction[Ph. D. Thesis][D]. Xi¢an：Xi¢an UniversityofTechnology，2008.(in Chinese))
[19]	王建秀，付慧仙，朱雁飞.基于地层损失的盾构沉降计算方法研究进展[J]. 地下空间与工程学报，2010，6(1)：112-119.(WANG Jianxiu，FU Huixian，ZHU Yanfei.Advance in calculation of subsidence causedby shield tunnelbased on strata loss[J]. Chinese Journal ofUnderground Space and Engineering，2010，6(1)：112-119.(in Chinese))
[20]	LOGANATHAN N，POULOS H G.Analytical prediction for tunneling-induced ground movement in clays[J]. Journal of Geotechnicaland Geoenviromental Engineering，1998，124(9)：846-856.
[21]	魏纲.盾构隧道施工引起的土体损失率取值及分布研究[J]. 岩土工程学报，2010，32(9)：1354-1361.(WEI Gang. Selection and distribution of ground loss ratio induced by shieldtunnel construction[J]. Chinese Journal of Geotechnical Engineering，2010，32(9)：1354-1361.(in Chinese))
[22]	邹翀. 盾构隧道同步注浆技术[J].现代隧道技术，2003，40(1)：26-30.(ZOU Chong. Synchronous grouting techniqueofShield tunneling[J].Modern Tunnelling Technology，2003，40(1)：26-30.(in Chinese))
[23]	张凤样，朱合华，傅德明.盾构隧道[M].北京：人民交通出版社，2004：400-405.(ZHANGFengxiang，ZHUHehua，FU Deming. Shield tunneling[M].Beijing：China Communication Press，2004：400-405.(in Chinese))