Research on Slope Stability Prediction Model Based on Topographic and Geomorphic Features

Abstract

In order to prevent slope collapse in time, this paper firstly collects topographic and geomorphological features to obtain macro and micro feature data such as slope gradient, slope direction and ground rate. Secondly, a model for predicting slope stability is established based on the obtained topographic and geomorphological data, and the topographic and geomorphological data are input into the model to predict the stability of the slope. Finally, through the prediction of the model, the value of slope stability is obtained, so that the imbalance of the slope can be prevented and the occurrence of accidents can be reduced. The results show that the predicted and actual coefficients of safety are 1.23 and 1.22 respectively at a slope of 8m with a low error. The prediction level of the model is better, the actual stability value and the predicted stability value are almost the same, and when predicting the horizontal displacement, the predicted displacement value and the actual displacement value are both 1.2, which can accurately predict the stability of the side. Compared with other models, the GM-RBF model has a safety state error of 0. The prediction model can reinforce the slope in time, reduce the cost of the project, and protect people's safety.