%0 Dataset
%T Depth learning model for prediction of shield tunneling speed in composite strata considering historical effects
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/35d689ce-86a8-4961-8a5e-dc754d1a8bb2
%W NCDC
%R 10.12072/ncdc.nieer.db2777.2023
%A None
%K Past operations;shield tunneling;advance rate prediction;deep learning;feature importance;mixed ground
%X <pre><code> This data set includes physical property parameters of materials used in the test, including weight, Poisson's ratio, cohesion, friction angle, deformation modulus and other parameters. The physical property parameters of the substances used in the test included in this data set are measured by the test equipment. The folder in the dataset contains an excel table. The tabular data includes physical property parameters of sand, conglomerate and mudstone, gravity, Poisson's ratio, cohesion, friction angle, deformation modulus, etc. The data volume is 10KB.