Stability prediction for soil-rock mixture slopes based on a novel ensemble learning model

Abstract

Soil-rock mixtures are geological materials with complex physical and mechanical properties. Therefore, the stability prediction of soil-rock mixture slopes using machine learning methods is an important topic in the field of geological engineering. This study uses the soil-rock mixture slopes investigated in detail as the dataset. An intelligent optimization algorithm-weighted mean of vectors algorithm (INFO) is coupled with a machine learning algorithm. One of the new ensemble learning models, which named IN-Voting, is coupled with INFO and voting model. Twelve single machine learning models and sixteen novel IN-Voting ensemble learning models are built to predict the stability of soil-rock mixture slopes. Then, the prediction accuracies of the above models are compared and evaluated using three evaluation metrics: coefficient of determination (R2), mean square error (MSE), and mean absolute error (MAE). Finally, an IN-Voting ensemble learning model based on five weak learners is used as the final model for predicting the stability of soil-rock mixture slopes. This model is also used to analyze the importance of the input parameters. The results show that: 1) Among 12 single machine learning models for the stability prediction of soil-rock mixture slopes, MLP (Multilayer Perceptron) has the highest prediction accuracy. 2) The IN-Voting model has higher prediction accuracy than single machine learning models, with an accuracy of up to 0.9846) The structural factors affecting the stability of soil-rock mixture slopes in decreasing order are the rock content, bedrock inclination, slope height, and slope angle.

Exploration and research on ammonium free green leaching agent for ionic rare earth ore and influencing factors of soil slope stability

“…Soil saturation is in uenced by local rainfall. In this paper, we control the rainfall condition in an ionic rare earth mine site by controlling the homemade rainfall environment simulation equipment, and compare the changes of friction and cohesion of strength index of unsaturated soil particles when rainfall is low and saturated soil particles when rainfall is high (Fu et al, 2023). For unsaturated soil particles, soil particle saturation increases with increasing rainfall, and soil slope stability decreases.…”