Hybrid Machine-Learning-Based Prediction Model for the Peak Dilation Angle of Rock Discontinuities.

ABSTRACT: The peak dilation angle is an important mechanical feature of rock discontinuities, which is significant in assessing the mechanical behaviour of rock masses. Previous studies have shown that the efficiency and accuracy of traditional experimental methods and analytical models in determining the shear dilation angle are not completely satisfactory. Machine learning methods are popular due to their efficient prediction of outcomes for multiple influencing factors. In this paper, a novel hybrid machine learning model is proposed for predicting the peak dilation angle. The model incorporates support vector regression (SVR) techniques as the primary prediction tools, augmented with the grid search optimization algorithm to enhance prediction performance and optimize hyperparameters. The propos

SUBMITTER: Xie S 

PROVIDER: S-EPMC10573530 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature