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Using Historical Data to Automatically Identify Air-Traffic Control Behavior
| 题名： | Using Historical Data to Automatically Identify Air-Traffic Control Behavior |
| 作者： | Lauderdale, T. A.; Wu, Y.; Tretto, C. |
| 关键词： | Air traffic control##Machine learning##Mathematical models##Routes##Air traffic##Controllers##Amount##Errors##Histories## |
| 摘要： | This project seeks to develop statistical-based machine learning models to characterize the types of errors present when using current systems to predict future aircraft states. These models will be data-driven - based on large quantities of historical data. Once these models are developed, they will be used to infer situations in the historical data where an air-traffic controller intervened on an aircraft's route, even when there is no direct recording of this action. |
| 总页数： | 34 |
| 报告类型： | 科技报告 |
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