舰船电子工程2025，Vol.45Issue(1)：43-47,5.DOI:10.3969/j.issn.1672-9730.2025.01.009
基于自适应卡尔曼滤波与LSTM的航班延误预测研究
Research on Flight Delay Prediction Based on Adaptive Kalman Filter and LSTM
摘要
Abstract
This study proposes a flight delay prediction model combining adaptive Kalman filtering(ACKF)and long short-term memory(LSTM)networks to improve prediction accuracy.While LSTM excels in capturing temporal dependencies,it struggles with extreme delay events.To address this,ACKF is incorporated to dynamically adjust predictions,enhancing the model's robustness.Experimental results show that the ACKF-LSTM model outperforms traditional LSTM and other models in metrics such as mean squared error(MSE)and root mean squared error(RMSE),significantly improving the accuracy of flight delay predictions.关键词
航班延误预测/卡尔曼滤波/LSTM/时间序列/深度学习Key words
flight delay prediction/Kalman filter/LSTM/time series analysis/deep learning分类
电子信息工程引用本文复制引用
罗凤娥,郭玲玉,杜裕鑫,卫昌波,徐勇..基于自适应卡尔曼滤波与LSTM的航班延误预测研究[J].舰船电子工程,2025,45(1):43-47,5.基金项目
中国民用航空局教育人才类项目"面向共建'一带一路'国家民航专业本科教育"(编号:MHJY2023021) （编号:MHJY2023021）
中国民用航空局教育人才类项目"基于能力导向培养的航空运行控制虚拟仿真实验中心建设"(编号:MHJY2022037) （编号:MHJY2022037）
中国民用航空飞行学院科研创新团队项目"航空运行控制技术研究所"(编号:JG2022-19,CZKY2023166)资助. （编号:JG2022-19,CZKY2023166）
