This study investigates the feasibility of implementing simple Machine Learning models to make fast and reliable predictions of rockfall energies and run-outs at the base of highwalls. Probabilistic rockfall simulations are performed to generate a synthetic dataset of rockfall trajectories using high-resolution 3D photogrammetric models of fifteen highwalls from open pit coal mines. An automated software solution is developed to extract 2D profiles along the full strike length of the highwalls and meaningful geometrical features are identified and quantified. Four representative highwalls are considered for the model calibration and the remaining walls are used for validation. The block release position, slope local roughness and average slope angle are chosen as input parameters, whereas the kinetic energy at the first impact, the first impact position and the final run-out of the blocks at the base of the highwall are used as target parameters in developing predictive models. The application of various regression models is investigated for each target parameter and their performances are compared. A multi-linear regression model shows the best predictions for the kinetic energy at the first impact at the base of the highwall, while the first impact position and the final rockfall run-out are better predicted by a multi-non-linear regression model. Overall, the models perform very similar. The results show reasonable applicability of the approach for a fast prediction of rockfall hazard for arbitrary highwalls based on the fully automatised extraction of geometrical features from 3D photogrammetric data.

中文翻译：

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使用基于回归的机器学习模型预测露天矿落石危险

本研究调查了实施简单的机器学习模型以快速可靠地预测高墙底部落石能量和跳动的可行性。使用来自露天煤矿的 15 个边墙的高分辨率 3D 摄影测量模型，进行概率落石模拟，生成落石轨迹的综合数据集。开发了一种自动化软件解决方案，用于沿边墙的整个走向长度提取二维剖面，并识别和量化有意义的几何特征。四个代表性的边墙被考虑用于模型校准，其余的边墙用于验证。选择块体释放位置、坡体局部粗糙度和平均坡度作为输入参数，以块体在边坡底部的第一次冲击动能、第一次冲击位置和最终跳动为目标开发预测模型时的参数。针对每个目标参数研究了各种回归模型的应用，并比较了它们的性能。多元线性回归模型显示了对边坡底部第一次撞击时动能的最佳预测，而多元非线性回归模型可以更好地预测第一次撞击位置和最终落石跳动。总体而言，这些模型的表现非常相似。结果表明，该方法具有合理的适用性，可基于从 3D 摄影测量数据中全自动提取几何特征来快速预测任意高墙的落石危险。