A Nonlinear Prediction Model of Antislide Pile Top Displacement Based on MIC-SVR for Jurassic Landslides

Abstract

In this study, a nonlinear prediction model of antislide pile top displacement is proposed. Based on the quantitative analysis of the rock mass structure characteristics of the soft and hard interbedded sliding bed in the Jurassic strata, the post-thrust force and geometric characteristics of the top of antislide pile displacement, and bending moment, the main controlling factors affecting the displacement of the top of antislide pile were determined by maximal information coefficient (MIC). Through orthogonal experiment design and 3DEC numerical experiment, a database of main controlling factors (sliding bedrock inclination, thrust size, embedded depth, and pile section size) of pile top displacement was established and a nonlinear prediction model of the displacement of the top of antislide pile based on the main controlling factors was proposed. Finally, two engineering examples were used to validate the performance of this model, with the comparisons of four prediction methods (SVR, MIC-SVR, LSTM, and ELMAN). The results show that the MIC-SVR model has a practical reference value for the prediction of the displacement of the top of an antislide pile in the Jurassic landslide in the Three Gorges Reservoir Area.