Intelligent Displacement Back Analysis Method of Three-Dimension Applied in Unsymmetrical Pressure Tunnel with Shallow Depth

Artificial neural network has been widely used in displacement back analysis, but it has the problems of large sample, over-fitting, local optimization and poor generalization performance, so it has the poor adaptability in the Geotechnical Engineering. Support Vector Machines algorithm has the advantages of small sample, global optimization and generalization performance. A direct optimization method based on genetic algorithm and the improved support vector regression algorithm (GA-SVR) is applied in order to identify multinomial parameters intelligently and forecast displacements fast and exactly, combined with an unsymmetrical pressure tunnel with shallow depth section of the left line of import in BEIKOU Tunnel on Zhangjiakou-Shijiazhuang highway. The application result shows the new type of intelligent displacement back analysis could obtain accurately the parameters of rock mechanics and initial stress in limited monitoring data and provide parameters for ahead-forecast of rock deformation.