Determination of stability of epimetamorphic rock slope using Minimax Probability Machine

Abstract

The article employs Minimax Probability Machine (MPM) for the prediction of the stability status of epimetamorphic rock slope. The MPM gives a worst-case bound on the probability of misclassification of future data points. Bulk density (d), height (H), inclination (β), cohesion (c) and internal friction angle (φ) have been used as input of the MPM. This study uses the MPM as a classification technique. Two models {Linear Minimax Probability Machine (LMPM) and Kernelized Minimax Probability Machine (KMPM)} have been developed. The generalization capability of the developed models has been checked by a case study. The experimental results demonstrate that MPM-based approaches are promising tools for the prediction of the stability status of epimetamorphic rock slope.