摘要
为了解决传统的空气动力学模型在预测四维飞行轨迹上误差较大的问题,提出一种基于数据挖掘的预测模型。该模型挖掘历史飞行时间数据,从中找出影响飞行时间的因素,预测出下一次飞行的全程时间,然后从历史位置数据中分析得出飞机在每个采样周期点上的位置,实现完整的四维轨迹预测。仿真试验验证了该模型预测的准确性和可用性。
Due to the large errors of traditional aerodynamic 4-D trajectory prediction models, a prediction model based on mining flight history data was proposed. Firstly, the factors that had impact on total flying time were found out from flying history, and the flying time of next flight was predicted. Then from the flying position data, the positions where aircraft was located in each sampling period were worked out, and the whole prediction 4-D trajectory was got. Simulation tests prove the accuracy and availability of this model.
出处
《计算机应用》
CSCD
北大核心
2007年第11期2637-2639,共3页
journal of Computer Applications
基金
国家863计划项目(2006AA12A104)
关键词
四维轨迹
数据挖掘
采样周期
预测
4-D trajectory
data mining
sample period
prediction
