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Machine Learning and Mass Estimation Methods for Ground-Based Aircraft Climb Prediction

机译：地基飞机爬升预测的机器学习和质量估计方法

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In this paper, we apply machine learning methods to improve the aircraft climb prediction in the context of ground-based applications. Mass is a key parameter for climb prediction. As it is considered a competitive parameter by many airlines, it is currently not available to ground-based trajectory predictors. Consequently, most predictors today use a reference mass that may be different from the actual aircraft mass. In previous papers, we have introduced a least squares method to estimate the mass from past trajectory points, using the physical model of the aircraft. Another mass estimation method, based on an adaptive mechanism, has also been proposed by Schultz We now introduce a new approach, in which the mass is considered the response variable of a prediction model that is learned from a set of example trajectories. This machine learning approach is compared with the results obtained when using the base of aircraft data (BADA) reference mass or the two state-of-the-art mass estimation methods. In these experiments, nine different aircraft types are considered. When compared with the baseline method (respectively, the mass estimation methods), the Machine Learning approach reduces the RMSE (Root Mean Square Error) on the predicted altitude by at least 58% (resp. 27%) when assuming the speed profile to be known, and by at least 29% (resp. 17%) when using the BADA speed profile except for the aircraft types E145 and F100. For these types, the observed speed profile is far from the BADA speed profile.
机译：在本文中，我们应用机器学习方法来改进基于地面应用的飞机的爬升预测。质量是爬升预测的关键参数。由于许多航空公司都将其视为竞争性参数，因此目前基于地面的轨迹预测器无法使用。因此，当今大多数预测器使用的参考质量可能与实际飞机质量不同。在先前的论文中，我们已经使用飞机的物理模型引入了最小二乘法来估计过去轨迹点的质量。舒尔茨还提出了另一种基于自适应机制的质量估计方法。我们现在介绍一种新方法，其中将质量视为从一组示例轨迹中获知的预测模型的响应变量。将这种机器学习方法与使用飞机数据（BADA）参考质量或两种最新质量估算方法时获得的结果进行比较。在这些实验中，考虑了九种不同的飞机类型。当与基线方法（分别是质量估计方法）相比时，如果假定速度曲线为，则机器学习方法将预测高度上的RMSE（均方根误差）降低至少58％（分别为27％）。已知，使用BADA速度曲线时至少要降低29％（分别为17％），但E145和F100型飞机除外。对于这些类型，观察到的速度曲线与BADA速度曲线相距甚远。

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