@inproceedings{2353f3cdca464e4fa561aa3f874444d5,
title = "FOBA: Flight Operation Behavior Analysis Based on Hierarchical Encoding",
abstract = "Through analyzing flight data we can detect pilot{\textquoteright}s improper operation, which effectively improves flight safety. This paper proposes an approach to convert multivariate flight data into symbol series and an auto-regressive semantic understanding model. Our model can predict what kind of pilot operation or aircraft status should appear at the next time step according to data at the current time step. Furthermore, we proposed a prediction model for unsafe event predicting based on our semantic understanding model. The experiment results show that our prediction model outperforms well known classifiers. Finally, experiments show that our model has the application value of correcting pilot operation.",
keywords = "Behavior encoding, Deep learning, Flight Event Predict",
author = "Tongyu Zhu and Zhiwei Tong",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021 ; Conference date: 14-08-2021 Through 16-08-2021",
year = "2021",
doi = "10.1007/978-3-030-82147-0\_17",
language = "英语",
isbn = "9783030821463",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "205--217",
editor = "Han Qiu and Cheng Zhang and Zongming Fei and Meikang Qiu and Sun-Yuan Kung",
booktitle = "Knowledge Science, Engineering and Management - 14th International Conference, KSEM 2021, Proceedings",
address = "德国",
}