Risk prediction of water inrush of karst tunnels based on BP neural network

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, underground 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 engineering 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.