基于随机森林的航空器到达时刻预测

航空器到达时刻（ ETA）预测是进场排序与调度的基础，因此进场飞行时间的快速与准确预测显得尤为重要。通过分析航班信息、天气信息以及空中交通信息，基于随机森林算法构建了航空器到达时刻预测模型。选取上海浦东机场进场航班进行仿真验证，仿真结果表明，预测模型可以实现航空器到达时刻的快速与准确预测。

Arrival Flight Time Prediction Based on OLS-RBF Neural Networks

Estimated Time of Arrival ( ETA) plays a great role in arrival sequencing and scheduling ,there-fore it is particularly important to predict the arrival flight time quickly and accurately .Through the in-depth analysis of flights data ,weather information and air traffic flow ,an estimated time of arrival predic-tion model was constructed based on Random Forest method .Taking the arrival flights to Shanghai Pudong Airport as examples ,the simulation was carried out .And the simulation result indicated that the proposed model was able to predict the estimated time of arrival quickly and accurately .