HIGHLIGHTS
SUMMARY
One approach that has gained significant attention in recent years is machine_learning. In contrast to machine_learning, physics-based models are built on the principles of mechanics and physics. Machine_learning-based prediction models can be highly effective at predicting the slope failure by training on large datasets and identifying the hidden patterns in the data. Traditional machine_learning models often have their limitations. To address these limitations, the authors proposed a machine_learning-based slope failure prediction model that considers the prediction result`s uncertainty. The model uses timeseries data to train a machine_learning algorithm and incorporates . . .
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