Research on fatigue detection of flight trainees based on face EMF feature model combination with PSO-CNN algorithm

Author:

Shang Lei,Si Haiqing,Wang Haibo,Pan Ting,Liu Haibo,Li Yixuan,Qiu Jingxuan,Xu Mengyue

Funder

Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics

Joint Fund of the National Natural Science Foundation of China and Civil Aviation Administration of China

the Fundamental Research Funds for the Central Universities

the Experimental Technology Research and Development" project of Nanjing University of Aeronautics and Astronautics Project

the first batch of industry-university-research cooperative collaborative education projects of the Ministry of Education in 2021

the Nanjing University of Aeronautics and Astronautics PhD short-term visiting scholar project

Publisher

Springer Science and Business Media LLC

Reference24 articles.

1. Lee, S. & Kim, J. K. Factors contributing to the risk of airline pilot fatigue. J. Air Transp. Manag. 67, 197–207 (2018).

2. Li, Y. et al. The influence of mindfulness on mental state concerning safety among civil pilots. J. Air Transp. Manag. 84, 101768 (2020).

3. Liu, H. et al. Flight training evaluation based on dynamic Bayesian network and fuzzy gray theory. Acta Aeronautica et Astronautica Sinica 42(08), 250–261 (2021).

4. Wang, R. & Gao, Z. X. Influencing factors of civil aircraft landing safety based on flight data. J. Transp. Inf. Saf. 37(04), 27–34 (2019).

5. Kelly, D. & Efthymiou, M. An analysis of human factors in fifty controlled flight into terrain aviation accidents from 2007 to 2017. J. Saf. Res. 69(6), 155–165 (2019).

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