Comprehensive Assessment Method Based on Blind Information Theory in Highway Tunnel Construction

Article Preview

Abstract:

In the highway tunnel construction, monitoring parameters are so various, and along with the construction uncertainties, it is very difficult to adopt one fixed model to generalize the complicated law of the monitoring information. Therefore, we choose data in different periods and assign the data with corresponding credibility respectively, and then the monitoring result is described using blind information. In this paper, the theory of blind information is introduced first, and then the blind information is applied in the engineering case of comprehensive assessment of tunnel safety monitoring. The research result has demonstrated that processing the monitored values by applying blind number can largely weaken uncertainty of the monitored information, and makes the evaluation of the construction safety issue more detailed and comprehensive, which overcomes the traditional methods’ defect that describes information too absolutely. The result indicates that blind data is valuable for comprehensive assessment of tunnel safety monitoring.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 639-640)

Pages:

287-292

Citation:

Online since:

January 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Zhang Q F,Wang J G, Li X H. Study on indefinite information in dam safety monitoring. Journal of Hehai University Natural Sciences.2002,30(5):113-117.

Google Scholar

[2] Zhang S,Tao S J,Liu Z N. Application of Prediction Model to Tunnel Monitoring,Journal of Geomatics,2011 (1):45-46.

Google Scholar

[3] Li G X, Li Z I, Zou W B. Fuzzy Evaluation on Transportation Tunnel with Confidence Factors, Safety and Environmental Engineering. 2001 (2):72-74.

Google Scholar

[4] Huang H. Safety Monitoring Theories and Technologies for Earth Rockfill Dam. Nan Jing Hehai University, 2005.

Google Scholar

[5] Huang K, Liu B C, Peng J G. Intelligent back-analysis of tunnel surrounding rock displacement based on genetic algorithm and neural network. Journal of Central South University(Science and Technology), 2011 (1):213-219.

Google Scholar

[6] Li J C, Liu Z J. Research on Displacement Back Analysis of Surrounding Rock of Tunnel Based on BP Neural Network. Soil Engineering and Foundation, 2011 (1):65-69.

Google Scholar