On the left bank of a hydropower station dam project diversion tunnel based on the extreme learning machine (ELM) is applied to the tunnel rock creep parameter inversion calculation. Through the orthogonal experimental design to determine 16 groups of rock mechanics parameters of diversion tunnel exit section, select one of the 14 groups using Cvisc FLAC3D model in numerical analysis, the calculation of creep parameters for each group and the corresponding of the displacement, the training of ELM network, the key point of rock displacement monitoring actual input the process line, the nonlinear relationship between the inversion of rock creep parameters determined two, the remaining two groups to test the training results. The model is applied to a hydropower station on the left bank of tunnel rock creep parameters inversion analysis, calculation results and the measured displacement values fitted well, which shows that the model is simple and practical, has good retrieval accuracy, which can meet the requirement of engineering design.