Application of Neural Network in Displacement Prediction of Dongping Tunnel

Abstract

It has been proved that Multi-layer network computing can solve the nonlinear separable problem, but the problem which the hidden layer makes the learning more difficult limits the development of multi-layer network.Back-propagation (BP) algorithm solve this problem and promote multi-network research to regain attention. In this paper, A new method which dynamic matrix control method based on neural network is found. Its essence is that the resulting prediction signal is produced by the manner which regards neural network model as prediction model, and the predictive control of nonlinear systems would be realized by the control law which using the receding optimization algorithm. Neural network Selects the BP neural network which possess a good nonlinear function approximation capability.Aiming at dongping tunnel surface deformation prediction, the article adopt BP Neural Network to train the system basing on the given data. It shows the hiding neural node is close to precision; predictive value in good agreement with measured values, and to some extent be able to guide the construction.