PROCEEDINGS OF TUNNEL ENGINEERING, JSCE
Online ISSN : 1884-9091
ISSN-L : 1345-0832
Affecting factor analysis of tunnel collapse magnitude using AI method
Kyoungwon SEOTsuyoshi DOMONTakeyuki SUZUKIKazuo NISHIMURA
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JOURNAL FREE ACCESS

2003 Volume 13 Pages 123-128

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Abstract
Tunnel collapses due to various reasons according to the state of ground and excavation conditions and condition of support. It is very difficult to predict and evaluate them and prepare the strengthening in advance.
This study deals with development of the prediction system of tunnel collapse magnitude and analysis of the causes affecting the magnitude of the collapse.
Based on the analysis of data in this study, the main cause of collapse magnitude, which is the output node, is topography around the tunnel.
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© by Japan Society of Civil Engineers
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