The Safety Classification Of Surrounding Rocks In Tunnels And Its Engineering Application Based On BP Neural Network

In this paper, the research trend and development situation of the safety classification of surrounding rocks at home and abroad is introduced at first. Since surrounding rocks in tunnels are geological comprehensive body which is subjected to the cut of various structural faces and there are many affecting factors, it is very hard to describe its relationship by one exact mathematic expression and it belongs to a high-degree nonlinear mapping problem. And Artificial Neural Network has the capacity of parallel managing the cosmical information, nonlinear mapping ability, high-degree error tolerance, self-suit and reasoning extensive capacity and other good characteristics. By studying and remembering, the nonlinear relationship of the input and output variable is established. And in this paper the BP neural network model of safety classification of surrounding rocks is established by MATLAB neural network toolbox based on the theory of Artificial Neural Network method and the model is applied into the safety classification of surrounding rocks of Dongshang tunnel in Huainan. And the result suggests that the precision of the model is high and meets the request of practical engineering project. In conclusion, the BP neural network model of safety classification of surrounding rocks is established by MATLAB neural network toolbox and this paper provides a referenced and easy method for the future safety classification of surrounding rocks by solving the complex programming course.