为了提高服务质量和降低运营成本,所有的航空公司都在不断寻找各种方法来合理安排航线,降低航班延误。本文主要讨论如何利用大数据来更准确地预测飞机时空位置和航班到达(跑道、登机口)时间,从而更有效地实时优化航班,使得总的延误时间与消耗燃油最小。在此过程中,研究细化航班调度涉及的目的与问题,在此基础上建立数学模型,最终通过机器学习技术求解此模型,提出合理的调度方法。 In order to improve service quality and reduce operating costs, all airlines are constantly looking for ways to make reasonable routes and reduce flight delays. This article focuses on how to make use of big data to predict more accurately the time and location of an aircraft and the arrival time of a flight (runway, gate) so as to optimize the flight more efficiently in real time so that the total delay time and fuel consumption are minimized. In this process, we study the purpose and problems involved in detailed flight scheduling. Based on this, a mathematical model is established. Finally, the model is solved by machine learning technology and a reasonable scheduling method is proposed.