Research on flight risk identification based on naive Bayes algorithm

Dawei Yin

doi:10.1117/12.3029086

22 May 2024 Research on flight risk identification based on naive Bayes algorithm

Dawei Yin

Proceedings Volume 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023); 1317606 (2024) https://doi.org/10.1117/12.3029086
Event: Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 2023, Hangzhou, China

Abstract

Left boundary flight training of trainer aircraft is usually accompanied by higher flight risk, therefore, it is very necessary to study flight risk identification of left boundary flight action. Based on flight training outline and expert decision-making, flight risk of left boundary is divided into three levels: low, medium and high. Considering strong independence of risk identification features, by using naive Bayes algorithm and typical flight parameters such as altitude, velocity and pitch angle and so on, probability distribution results of flight parameters risk evaluation indexes corresponding to different risk levels are obtained to form risk labels. According to probability distribution of risk evaluation index, actual flight risk grade of left boundary flight action is identified by means of maximum likelihood method.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Dawei Yin "Research on flight risk identification based on naive Bayes algorithm", Proc. SPIE 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 1317606 (22 May 2024); https://doi.org/10.1117/12.3029086

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