Evaluation of compaction quality of earth-rock dam based on bacterial foraging-support vector regression algorithm

DOI

10.2991/imst-16.2016.39How to use a DOI?

Keywords

evaluation of compaction quality, earth-rock dam, support vector regression, bacterial foraging algorithm.

Abstract

Compaction quality is an important part of quality assessment of earth-rock dam. Current evaluation methods tend to use the graphical reports of compaction parameters based on real-time compaction monitoring system, or built compaction quality prediction model, such as the multiple linear regression model and the neural network model, to evaluate compaction quality of storehouse surface. However, the precision of these models is not enough. In this study the bacterial foraging -support vector regression algorithm is proposed and employed to establish a high prediction model between multiple attributes and compactness to evaluate compaction quality of storehouse surface. This compaction quality evaluation method gets rid of the one-sided shortcomings of the compaction graphical reports, and greatly improve the prediction accuracy compared with current models, which provides reasonable compaction quality evaluations for quality management works.

Copyright

© 2016, 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  - Jiajun Wang
AU  - Denghua Zhong
AU  - Fei Wang
PY  - 2016/11
DA  - 2016/11
TI  - Evaluation of compaction quality of earth-rock dam based on bacterial foraging-support vector regression algorithm
BT  - Proceedings of the 2016 International Conference on Innovative Material Science and Technology (IMST 2016)
PB  - Atlantis Press
SP  - 265
EP  - 270
SN  - 1951-6851
UR  - https://doi.org/10.2991/imst-16.2016.39
DO  - 10.2991/imst-16.2016.39
ID  - Wang2016/11
ER  -