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http://dx.doi.org/10.12989/acd.2017.2.2.121

Collapse risk evaluation method on Bayesian network prediction model and engineering application  

WANG, Jing (Research Center of Geotechnical and Structural Engineering, Shandong University)
LI, Shucai (Research Center of Geotechnical and Structural Engineering, Shandong University)
LI, Liping (Research Center of Geotechnical and Structural Engineering, Shandong University)
SHI, Shaoshuai (Research Center of Geotechnical and Structural Engineering, Shandong University)
XU, Zhenhao (Research Center of Geotechnical and Structural Engineering, Shandong University)
LIN, Peng (Research Center of Geotechnical and Structural Engineering, Shandong University)
Publication Information
Advances in Computational Design / v.2, no.2, 2017 , pp. 121-131 More about this Journal
Abstract
Collapse was one of the typical common geological hazards during the construction of tunnels. The risk assessment of collapse was an effective way to ensure the safety of tunnels. We established a prediction model of collapse based on Bayesian Network. 76 large or medium collapses in China were analyzed. The variable set and range of the model were determined according to the statistics. A collapse prediction software was developed and its veracity was also evaluated. At last the software was used to predict tunnel collapses. It effectively evaded the disaster. Establishing the platform can be subsequent perfect. The platform can also be applied to the risk assessment of other tunnel engineering.
Keywords
76 large or medium collapses; Bayesian network; prediction model of collapse; collapse prediction software; engineering application;
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Times Cited By KSCI : 3  (Citation Analysis)
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