Abstract | Airlines prepare and update their operation plan pre-tactically (D-1) to identify which flights might require intervention during the day (e.g. potential aircraft swaps or cancellations). Deviations between their plan and the execution could be related to many factors, and in particular to Air Traffic Flow Management (ATFM) regulations. A collection of machine learning models, developed within Dispatcher3, a CleanSky2 innovation action, can be used to estimate which flights are likely to be affected by ATFM regulations and the potential impact of these delays. The outcome of these individual models is integrated into higher-level interpretable predictions in an advice generator to be used pre-tactically. |
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