Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)

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Regression Analysis for Soft Rock Tunnel Monitoring Data Based on Data-Mining by SPSS

Authors
Jiejun TANG
Corresponding Author
Jiejun TANG
Available Online September 2012.
DOI
10.2991/emeit.2012.162How to use a DOI?
Keywords
SPSS,vault sink,surrounding convergence,regression analysis,soft rock tunnel
Abstract

Using SPSS software for pretreated soft rock tunnel, a regression analysis of the monitoring data reflected the internal relationship and change rule between tunnel vault sink and the surrounding convergence and distance from tunnel face to monitoring section and measuring time. The results show that: the regression model of soft rock tunnel fitted well to monitoring data, under different adjacent rock condition the corresponding tunnel deformation model has big difference, according to the fitting regression equation of tunnel monitoring data, we can preliminary calculate the limit value of tunnel excavation after excavating and the time needed until stable state to provide strong basis for adjusting performed deformation and later arrangement.

Copyright
© 2012, 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 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
Series
Advances in Intelligent Systems Research
Publication Date
September 2012
ISBN
10.2991/emeit.2012.162
ISSN
1951-6851
DOI
10.2991/emeit.2012.162How to use a DOI?
Copyright
© 2012, 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

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TY  - CONF
AU  - Jiejun TANG
PY  - 2012/09
DA  - 2012/09
TI  - Regression Analysis for Soft Rock Tunnel Monitoring Data Based on Data-Mining by SPSS
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 763
EP  - 767
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.162
DO  - 10.2991/emeit.2012.162
ID  - TANG2012/09
ER  -