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Machine Learning Approach to Predict Aircraft Landing Times using Mediated Predictions from Existing Systems.
| 题名： | Machine Learning Approach to Predict Aircraft Landing Times using Mediated Predictions from Existing Systems. |
| 作者： | Dan Wesely ##Andrew Churchill ## John Slough##William J. Coupe |
| 摘要： | We developed a novel approach for predicting the landing time of airborne flights in real- time operations. The first step predicts a landing time by using mediation rules to select from among physics-based predictions (relying on the expected flight trajectory) already available in real time in the Federal Aviation Administration System Wide Information Management system data feeds. The second step uses a machine learning model built upon the mediated predictions. Themodelistrainedtopredicttheerrorinthemediatedprediction, usingfeatures describing the current state of an airborne flight. These features are calculated in real time from a relatively small number of data elements that are readily available for airborne flights. Initialresultsbasedonfivemonthsofdataatsixlargeairportsdemonstratethatincorporatinga machinelearningmodelontopofthemediatedphysics-basedpredictioncanleadtosubstantial additional improvements in prediction quality. |
| 总页数： | 22 |
| 报告类型： | 科技报告 |
| 发布日期： | 2021 |
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