Performance prediction of tunnel boring machine through developing high accuracy equations: A case study in adverse geological condition
作者: Masoud SamaeiMasoud RanjbarniaVahid NouraniMasoud Zare Naghadehi
作者单位: 1Department of Geotechnical Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
2Center of Excellence in Hydroinformatics, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
3Faculty of Civil and Environmental Engineering, Near East University, Nicosia, Turkey
4Department of Mining and Metallurgical Engineering, University of Nevada, Reno, USA
刊名: Measurement, 2019
来源数据库: Elsevier Journal
DOI: 10.1016/j.measurement.2019.107244
关键词: TBM performance predictionQueens tunnelGenetic Expression Programming (GEP)Classification and Regression Tree (CART)Fourier regression
英文摘要: Abstract(#br)The aim of present study is to propose new superior equations and introduce novel techniques for TBM performance prediction. To this end, correlations between the Rate of Penetration (ROP) and rock mass properties are investigated using four simple regression analyses. Based on these analyses, two non-linear multivariable equations are introduced and optimized by the Imperialist Competitive Algorithm (ICA). Then, two other distinct models are examined by using the Classification and Regression Tree (CART) and Genetic Expression Programming (GEP) techniques. The aforementioned methods are applied on a dataset from the Queens Tunnel, in New-York City with complex geology conditions. It was found that the models proposed by ICA, CART and GEP techniques have determination...
全文获取路径: Elsevier  (合作)
影响因子:1.13 (2012)

  • prediction 预报
  • geological 地质的
  • tunnel 坑道
  • developing 显影
  • regression 海退
  • boring 钻进
  • accuracy 准确度
  • machine 机器
  • TBM 隧道掘进机
  • through 经过