G. Enea and M. Porretta, A comparison of 4D-trajectory operations envisioned for nextgen and sesar, some preliminary findings, pp.23-28, 2012.

, Dart-data-driven aircraft trajectory prediction research

M. G. Hamed, D. Gianazza, M. Serrurier, and N. Durand, Statistical prediction of aircraft trajectory: regression methods vs point-mass model, ATM Seminar, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00911709

W. Kun and P. Wei, A 4-d trajectory prediction model based on radar data, Control Conference, 2008. CCC 2008. 27th Chinese, pp.591-594, 2008.

A. De-leege, M. Van-paassen, and M. Mulder, A machine learning approach to trajectory prediction, AIAA Guidance, Navigation, and Control (GNC) Conference, p.4782, 2013.

S. Hong and K. Lee, Trajectory prediction for vectored area navigation arrivals, Journal of Aerospace Information Systems, vol.12, issue.7, pp.490-502, 2015.

K. Tastambekov, S. Puechmorel, D. Delahaye, and C. Rabut, Aircraft trajectory forecasting using local functional regression in sobolev space, Transportation research part C: emerging technologies, vol.39, pp.1-22, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00924360

M. G. Karlaftis and E. I. Vlahogianni, Statistical methods versus neural networks in transportation research

, Differences, similarities and some insights, Transportation Research Part C: Emerging Technologies, vol.19, pp.387-399, 2011.

Y. , L. Fablec, and J. Alliot, Using neural networks to predict aircraft trajectories, IC-AI, pp.524-529, 1999.

R. Alligier, D. Gianazza, and N. Durand, Machine learning applied to airspeed prediction during climb, ATM seminar 2015, 11th USA/EUROPE Air Traffic Management R&D Seminar, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01168664

, Machine learning and mass estimation methods for ground-based aircraft climb prediction, IEEE Transactions on Intelligent Transportation Systems, vol.16, issue.6, pp.3138-3149, 2015.

Z. Wang, M. Liang, and D. Delahaye, Short-term 4d trajectory prediction using machine learning methods, SID 2017, 7th SESAR Innovation Days, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01652041

Y. Bengio and Y. Lecun, Scaling learning algorithms towards ai, vol.34, pp.1-41, 2007.

, Report on national civil aviation flight operation efficiency in 2017 (chinese), Tech. Rep, 2018.

, Electronic Aeronautical Information Publication of People's Republic of China, Aeronautical Information Center, 2017.

A. Krizhevsky, I. Sutskever, and G. E. Hinton, Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, pp.1097-1105, 2012.
DOI : 10.1145/3065386
URL : http://dl.acm.org/ft_gateway.cfm?id=3065386&type=pdf

D. P. Kingma and J. Ba, Adam: A method for stochastic optimization, 2014.

A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang et al., Automatic differentiation in pytorch, 2017.

S. Haykin, Neural networks: a comprehensive foundation, 1994.