Machine learning algorithms aim to improve the power of predictors over conventional regression models. This study aims to tap the predictive potential of crash mechanism-related variables using ensemble machine learning models. The results demonstrate selected models can predict severity at a high level of accuracy. The stacking model with a linear blender is preferred for the designed ensemble combination. Most bagging, boosting, and stacking algorithms perform well, indicating ensemble models are capable of improving upon individual models.

中文翻译：

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基于两车碰撞机理的机器学习和集成模型伤害严重程度预测

机器学习算法旨在提高预测器相对于传统回归模型的功能。这项研究旨在利用整体机器学习模型挖掘与碰撞机制相关的变量的预测潜力。结果表明，所选模型可以高度准确地预测严重性。对于设计的整体组合，最好使用带有线性搅拌器的堆叠模型。大多数装袋，提升和堆叠算法的性能都很好，这表明集成模型能够对单个模型进行改进。