Identifying geomechanical parameters of high cut rock slopes by an improved multi-output support vector machine method

Abstract

Mechanical parameters of geomaterials are very important to slope stability assessment, design, and safety construction. Back analysis is a practical engineering tool which is commonly used to identify geomechanical parameters based on monitored displacement during slope excavation. The key problem is to establish the nonlinear relationship between geomechanical parameters and the monitored displacements at different excavation steps. This paper presents an improved multi-output support vector machine (MSVM) method which integrates the artificial bee colony algorithm (ABC), numerical analysis, and updated displacement monitoring. MSVM was used to map the complex relationship between geomechanical parameters and slope displacement increments. Training samples were chosen following a Latin hypercube model and their data were applied to numerical model. ABC formed the back analysis, searching for optimal geomechanical parameters based on the MSVM model and field-monitored displacement. The proposed method was applied to a high abutment steep rock slope of the Longtan hydropower station in China and successfully represented the relationship between geomechanical parameters and displacement increments. Updating the displacements at different excavation steps improved the precision of recognition. Reasonable mechanical parameters were identified and adopted in the slope stability analysis.