Abstract:In this paper, a method for predicting the deformation of rock surrounding a tunnel is put forward based on the weighted composite quantile autoregressive model, giving the principle and algorithm of the method. Using a case study of Yangzong tunnel in Kunming, the weighted composite quantile autoregressive prediction model is calculated and compared with other models. The results show that the forecast effect is better than that of the AR(2) model of the non-weighted composite quantile estimation, the auto regression prediction based on least square parameter estimation, the support vector machine optimized by genetic algorithm and some other prediction methods.
WANG Jiangrong. Application of Weighted Composite Quantile Autoregressive Model in Processing of Rock Surrounding Tunnel Displacement Data[J]. jgg, 2017, 37(5): 511-515.