Bayes discriminant analysis method for predicting the stability of open pit slope

Abstract

A method to forecast the stability of open pit slope by using the Bayes discriminant analysis theory is presented in this paper. The Bayes discriminant analysis theory was introduced firstly. Then considering the mining circumstances and geological conditions of open pit slope, six factors reflecting the stability of open pit slope, including the magnitude of unit weight, angle of internal friction, cohesion, slope angle, slope height and pore pressure ratio, were selected to establish a BDA model. 33 samples of open pit slope were used as the training and forecasting samples. The prior probability of each collectivity was obtained according to the ratio of training samples and re substitution method was also introduced to verify the stability of model. Compared with the support vector machine (SVM) method, the results show that this Bayes discriminant analysis model has excellent performance, high prediction accuracy and can be used in practical engineering.