Proceedings of the 2017 3rd International Forum on Energy, Environment Science and Materials (IFEESM 2017)

Construction Risk Analysis of Subway Station Based on Bayesian Network

Authors
Shiwei Hou, Xin Zhang, Zhiguo Xin, Xueli Zhang
Corresponding Author
Shiwei Hou
Available Online February 2018.
DOI
10.2991/ifeesm-17.2018.68How to use a DOI?
Keywords
Subway Station; Risk Analysis; Bayesian Network; Sensitivity Analysis
Abstract

The subway station construction risk factors of uncertainty is researched based on Bias network theory, the safety risk of metro station foundation is analyzed taking a metro station in Shenyang as an example. The possible risk factors for the construction process of subway station was collected combined with the actual engineering situation. The risk factors to establish a priori probability parameters Bayesian network model is constructed, and operation analysis by forward reasoning Bayesian network model is presented. The results show that the overall probability level is III, the most sensitive risk factors for foundation is pit surrounding buildings settlement and displacement.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 3rd International Forum on Energy, Environment Science and Materials (IFEESM 2017)
Series
Advances in Engineering Research
Publication Date
February 2018
ISBN
978-94-6252-453-8
ISSN
2352-5401
DOI
10.2991/ifeesm-17.2018.68How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Shiwei Hou
AU  - Xin Zhang
AU  - Zhiguo Xin
AU  - Xueli Zhang
PY  - 2018/02
DA  - 2018/02
TI  - Construction Risk Analysis of Subway Station Based on Bayesian Network
BT  - Proceedings of the 2017 3rd International Forum on Energy, Environment Science and Materials (IFEESM 2017)
PB  - Atlantis Press
SP  - 361
EP  - 366
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifeesm-17.2018.68
DO  - 10.2991/ifeesm-17.2018.68
ID  - Hou2018/02
ER  -