文章摘要
潘宇平, 倪静, 李林, 耿雪玉.基于LIB-SVM的盾构隧道地表沉降预测方法研究Journal of Water Resources and Water Engineering[J].,2018,29(3):231-235
基于LIB-SVM的盾构隧道地表沉降预测方法研究
Prediction method of ground surface settlement caused by shield tunnel construction based on LIB-SVM
  
DOI:10.11705/j.issn.1672-643X.2018.03.39
中文关键词: 盾构隧道  地表沉降  支持向量机  沉降预测
英文关键词: shield tunnel  ground surface settlement  support vector machine  settlement prediction
基金项目:国家自然科学基金项目(51608323、51678319); 上海市科学技术委员会青年英才“扬帆计划”项目(15YF1408200); 山东省自然科学基金项目(ZR2016EEM40)
Author NameAffiliation
PAN Yuping1, NI Jing1, LI Lin2, GENG Xueyu3 (1.上海理工大学 环境与建筑学院, 上海 200093 2.上海隧道股份有限公司, 上海 2000823.英国华威大学 工程学院, 考文垂 CV4 7AL) 
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中文摘要:
      在大数据开源的背景下,为了分析及预测隧道施工盾构掘进引起地表沉降,同时容纳较多影响地表沉降的因素,提高沉降预测的准确性,本文在总结归纳支持向量机的建模原理的基础上,将支持向量机(support vector machine,SVM)方法应用到地表沉降预测中。结合虹梅南路隧道西线工程,选取土体参数、盾构参数和隧道埋深等8个影响因素作为输入特征,地表最终沉降量作为输出目标值,通过交叉验证选取LIB-SVM的最优参数组合并建立预测模型,对盾构施工引起的地表沉降进行了预测,并与实测数据进行了对比。结果表明:预测结果与工程实际情况较吻合,误差基本在5%以内,证明了该方法在盾构施工引起地表沉降的实际预测中具有可行性,为隧道工程的研究提供了一条新途径。
英文摘要:
      Under the background of open sourcing big database, in order to analyze and predict the ground surface subsidence caused by shield tunneling in the tunnel construction, and to accommodate more factors that affect the ground surface settlement and improve the accuracy of settlement prediction, this paper summarized the modeling principles of support vector machines. Based on this, the support vector machine (SVM) was applied to the ground surface settlement prediction in this paper. A case study was carried out on the South Hongmei Road Tunnel construction with eight factors selected as input features including soil parameters, shield parameters, tunnel depth, etc., and the ultimate ground surface settlement was selected as the output target value. Cross validation was used to determine the optimal parameters of LIB-SVM and afterwards the prediction model was established. The ground surface settlement caused by shield tunnel construction was predicted and compared with the in situ measurement. The results showed that the data measurement is almost reproduced by the prediction with an error within 5%. The outcome of this research indicates that the SVM method is feasible in practical prediction in the ground surface settlement caused by shield tunnel construction, which offers a new approach on the research of the tunnel engineering.
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