Risk prediction of water inrush of karst tunnels based on BP neural network
- 10.2991/mmme-16.2016.74How to use a DOI?
- karst tunnel; water inrush; BP neural network; risk prediction; advanced geological prediction
To evaluate precisely the risk level of karst tunnel helps reduce the risk of sudden flood water accidents in the process of tunnel construction. On the basis of relevant literature, statistical study and comprehensive analysis of hydrogeological condition in karst tunnel, and select unfavorable geology, formation lithology, under-ground water level, topography and geomorphology, strata dip Angle, fracture of surrounding rock as risk evaluation index of karst tunnel water gushing. In different hydrogeological conditions, varies a lot. Using BP neural network method to analysis water gushing risk of karst tunnel and avoid the weight of factors. In engi-neering applications, assess water risk of tunnel by method of BP neural network, avoid the occurrence of sudden flood water, which provides reference for risk prediction of water gushing in karst tunnel.
- © 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/).
Cite this article
TY - CONF AU - Zhuo Yang PY - 2016/10 DA - 2016/10 TI - Risk prediction of water inrush of karst tunnels based on BP neural network BT - Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering PB - Atlantis Press SP - 327 EP - 330 SN - 2352-5401 UR - https://doi.org/10.2991/mmme-16.2016.74 DO - 10.2991/mmme-16.2016.74 ID - Yang2016/10 ER -