Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

被引：130

作者：

Santos, Ovidio J. ^{[1
]}

Celestino, Tarcisio B. ^{[1
]}

机构：

[1] Univ Sao Paulo, Dept Geotech, Sao Carlos Engn Sch, SGS, BR-13566590 Sao Carlos, SP, Brazil

来源：

TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY | 2008年 / 23卷 / 05期

基金：

巴西圣保罗研究基金会;

关键词：

underground excavation; neural network; settlements; subway; tunnels; instrumentation; sequential excavation;

D O I：

10.1016/j.tust.2007.07.002

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：481 / 491

页数：11

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