Abstract
In this study, the objective was to develop a new and highly-accurate artificial intelligence model for slope failure prediction in open-pit mines. For this purpose, the M5Rules algorithm was combined with a genetic algorithm (GA) in a novel hybrid technique, named M5Rules–GA model, for slope stability estimation and analysis and 450-slope observations in an open-pit mine in Vietnam were modeled using the Geo-Studio software based on essential parameters. The factor of safety was used as the model outcome. Artificial neural networks (ANN), support vector regression (SVR), and previously introduced models (such as FFA-SVR, ANN-PSO, ANN-ICA, ANN-GA, and ANN-ABC) were also developed for evaluating the proposed M5Rules–GA model. The evaluation of the model performance involved applying and computing the determination coefficient, variance account for, and root mean square error, as well as a general ranking and color scale. The results confirmed that the proposed M5Rules–GA model is a robust tool for analyzing slope stability. The other investigated models yielded less robust performance under the evaluation metrics.
Highlights
M5Rules and genetic algorithm (GA)In this study, eight Artificial intelligence (AI) techniques were used to develop slope failure predictive models, including Artificial neural networks (ANN), support vector regression (SVR), M5Rules, particle swarm optimization (PSO), firefly algorithms (FFA), ICA, ABC, and GA
The details for ANN, PSO, FFA, ICA, ABC, and SVR techniques were presented in many previous works[19,55,56,57,58,59,60]
As recommended in previous studies56,77,78, 80% of the database was used for the training of the models; the remaining 20% was used to assess the models’ performance
Summary
M5Rules and GAIn this study, eight AI techniques were used to develop slope failure predictive models, including ANN, SVR, M5Rules, PSO, FFA, ICA, ABC, and GA. A novel hybrid model, namely M5Rules–GA, for predicting slope stability (i.e., FOS) using a genetic algorithm (GA) and M5Rules was proposed and investigated in this study. Several ANNs, support-vector regression (SVR), and previously introduced slope stability prediction models (such as FFA-SVR, ANN-PSO, ANN-ICA, ANN-GA, and ANN-ABC) were implemented for a comprehensive comparison of the proposed M5Rules–GA model.
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