Study on prediction of cement-soil gravity retaining wall security risk based on BP

DOI

10.2991/csss-14.2014.60How to use a DOI?

Keywords

cement-soil gravity retaining wall; safety forecast ;BP neural network

Abstract

In order to forecast the security risk of cement-soil gravity wall, an index system whose function is to forecast the security of cement-soil gravity wall is established from four aspects of soil properties, mechanical properties of mixer, materials, error of a pile position and verticality deviation. We introduce BP neural network to the training of sample data, then BP neural network model is established to predict the security risk of cement-soil gravity retaining wall. Combined with a base engineering project, the validity and practicability of this forecast is testified.

Copyright

© 2014, 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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TY  - CONF
AU  - Cai-hui Li
PY  - 2014/06
DA  - 2014/06
TI  - Study on prediction of cement-soil gravity retaining wall security risk based on BP
BT  - Proceedings of the 3rd International Conference on Computer Science and Service System
PB  - Atlantis Press
SP  - 258
EP  - 260
SN  - 1951-6851
UR  - https://doi.org/10.2991/csss-14.2014.60
DO  - 10.2991/csss-14.2014.60
ID  - Li2014/06
ER  -