基于数字孪生的航班延误时间预测方法
Flight Delay Time Prediction Method Based on Digital Twins
丁建立 1黄辉 1曹卫东1
作者信息
摘要
为了更加准确和高效地预测大面积航班延误时间,提出了基于数字孪生的航班延误时间预测方法.首先,从航班链整体的角度出发,依据航班运行业务特点和数字孪生技术特征设计了航班链数字孪生系统框架,综合航班链全生命周期内相关航班和机场的运行状态特征;其次,基于Fastformer和GraphSAGE模型设计了航班链时空特征提取模型(ST-Former),充分挖掘航班之间的时空关联特征.实验表明,该方法预测效率和准确度显著提升,平均预测误差在3 min左右.
Abstract
In order to predict flight delays in large areas more accurately and efficiently,a flight delay pre-diction method based on digital twins is proposed.First,from the perspective of the flight chain as a whole,a flight chain digital twin system framework was designed based on the flight operation business characteristics and digital twin technology characteristics,integrating the operating status characteristics of relevant flights and airports during the entire life cycle of the flight chain.Secondly,a flight chain digital twin system framework was designed based on the Fastformer and GraphSAGE models designed a flight chain spatio-temporal feature extraction model(ST-Former)to fully explore the spatio-temporal correla-tion features between flights.Experiments showed that the prediction efficiency and accuracy of this meth-od were significantly improved,and the average prediction error was within 3 minutes.
关键词
航班延误预测/数字孪生/时空关联特征/Fastformer/GraphSAGEKey words
flight delay prediction/digital twin/spatio-temporal feature/Fastformer/GraphSAGE引用本文复制引用
基金项目
国家自然科学基金重点项目(U2233214)
国家自然科学基金重点项目(U2033205)
出版年
2024
NETL
NSTL
万方数据