计算机应用研究2024，Vol.41Issue(11)：3409-3414,6.DOI:10.19734/j.issn.1001-3695.2024.03.0098
基于小波重构-Autoformer的无人机融合空域饱和流量预测
Saturation flow prediction method for UAV in fusion airspace based on wavelet reconstruction-Autoformer
摘要
Abstract
To achieve the prediction of UAV saturation flow in fusion airspace,this paper proposed a UAV saturation flow pre-diction method based on wavelet reconstruction-Autoformer(WR-Autoformer).Initially,traffic flow data was decomposed using wavelet transformation to mitigate the impact of noise and highlight data characteristics.Subsequently,it utilized the Au-toformer model's deep decomposition mechanism and autocorrelation mechanism for foundational prediction.Considering the key factors affecting saturation flow,it introduced three UAV traffic correction coefficients.Finally,it outputted the UAV satu-ration flow prediction for fusion airspace by combining the UAV saturation flow calculation method.Upon verification,the WR-Autoformer model has reduced the average absolute error and mean squared error by 13％to 48％in 48 h and 96 h fore-casts,and the predicted saturation flow has increased by 36％to 38％compared to the current state.The experimental results prove that the proposed model can achieve accurate predictions and enhance the saturation flow of UAV in fusion airspace,while the vertical separation of UAV meets the safety requirements for class A aircraft.关键词
航空运输/无人机/饱和流量预测/小波重构/Autoformer/融合空域Key words
air transportation/UAV/prediction of saturation flow/wavelet reconstruction/Autoformer/fusion airspace分类
交通工程引用本文复制引用
乔英聪,马昕,陈相佐,马熊..基于小波重构-Autoformer的无人机融合空域饱和流量预测[J].计算机应用研究,2024,41(11):3409-3414,6.基金项目
中国民用航空局安全能力项目(2022237) （2022237）
