航班运行过程的动态性导致延误实时预测成为难题,动态数据驱动方法为其提供了一种解决方案.该方法能将航班运行实时数据动态加入延误预测过程中,使预测结果更准确可靠.以预测连续进港航班的降落延误为例,对航班之间的延误传递过程进行分析,建立相应的状态空间模型；给出动态数据驱动的航班延误预测框架及预测过程.在航班运行历史数据上进行的多个实验表明:该方法能获得较高的预测准确度和良好的预测稳定性.%Flight delay prediction remains an important research topic due to the dynamics in flight operating process. To solve this problem dynamic data-driven approach from control area was introduced, where real-time data was collected and injected into the prediction process to get more accurate and reliable result. In case of predicting the landing delays of continuous arrival flights, delay propagation was analyzed to establish the corresponding state space model. Then dynamic data-driven prediction architecture for flight delay and the prediction steps on this architecture were presented. Several experiments were carried out on the historic flight data to validate the performance of this solution. Results show that; the accuracy is high, and it is not sensitive to the number of continuous arrival flights. Therefore, the solution has good predictive stability and reliability.
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