R. Alligier, D. Gianazza, and N. Durand, Machine learning applied to airspeed prediction during climb, in: ATM seminar 2015, 2015.

D. Arthur and S. Vassilvitskii, k-means++: The advantages of careful seeding, Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, pp.1027-1035, 2007.

S. Ayhan and H. Samet, DICLERGE, Proceedings of the 8th ACM SIGSPATIAL International Workshop on Computational Transportation Science , IWCTS'15, 2015.
DOI : 10.1145/233269.233324

, Report on National Civil Aviation Flight Operation Efficiency in 2017 (Chinese), CAAC Operation Monitoring Center, 2018.

J. Chen, R. Wang, L. Liu, and J. Song, Clustering of trajectories based on Hausdorff distance, 2011 International Conference on Electronics, Communications and Control (ICECC), pp.1940-1944, 2011.
DOI : 10.1109/ICECC.2011.6066483

A. Eckstein, Automated flight track taxonomy for measuring benefits from performance based navigation, 2009 Integrated Communications, Navigation and Surveillance Conference, pp.1-12, 2009.
DOI : 10.1109/ICNSURV.2009.5172835

M. Ester, H. P. Kriegel, J. Sander, and X. Xu, A density-based algorithm for discovering clusters in large spatial databases with noise, pp.226-231, 1996.

F. and E. , Common trajectory prediction structure and terminology in support of SESAR & NextGen, 2010.

M. Gariel, A. N. Srivastava, and E. Feron, Trajectory Clustering and an Application to Airspace Monitoring, IEEE Transactions on Intelligent Transportation Systems, vol.12, issue.4, pp.1511-1524, 2011.
DOI : 10.1109/TITS.2011.2160628

X. Guan, X. Zhang, D. Han, Y. Zhu, J. Lv et al., A strategic flight conflict avoidance approach based on a memetic algorithm, Chinese Journal of Aeronautics, vol.27, issue.1, pp.93-101, 2014.
DOI : 10.1016/j.cja.2013.12.002

S. Hong and K. Lee, Trajectory Prediction for Vectored Area Navigation Arrivals, Journal of Aerospace Information Systems, vol.12, issue.7, 2015.
DOI : 10.1002/0471249688

M. Hrastovec and F. Solina, Prediction of aircraft performances based on data collected by air traffic control centers, Transportation Research Part C: Emerging Technologies, vol.73, pp.167-182, 2016.
DOI : 10.1016/j.trc.2016.10.018

J. Kaneshige, J. Benavides, S. Sharma, L. Martin, R. Panda et al., Implementation of a trajectory prediction function for trajectory based operations, 2014.

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

A. D. Leege, M. V. Paassen, and M. Mulder, A Machine Learning Approach to Trajectory Prediction, AIAA Guidance, Navigation, and Control (GNC) Conference, 2013.
DOI : 10.1109/DASC.2009.5347547

J. Macqueen, Some methods for classification and analysis of multivariate observations, Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, pp.281-297, 1967.

F. Nicol and S. Puechmorel, Unsupervised aircraft trajectories clustering: a minimum entropy approach, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01367590

A. Nuic, D. Poles, and V. Mouillet, BADA: An advanced aircraft performance model for present and future ATM systems, International Journal of Adaptive Control and Signal Processing, vol.24, issue.10, pp.850-866, 2010.
DOI : 10.1002/acs.1176

M. Porretta, M. D. Dupuy, W. Schuster, A. Majumdar, and W. Ochieng, Performance Evaluation of a Novel 4D Trajectory Prediction Model for Civil Aircraft, Journal of Navigation, vol.2993, issue.03, pp.393-420, 2008.
DOI : 10.3141/1788-08

A. Reynaldi, S. Lukas, and H. Margaretha, Backpropagation and Levenberg-Marquardt Algorithm for Training Finite Element Neural Network, 2012 Sixth UKSim/AMSS European Symposium on Computer Modeling and Simulation, pp.89-94, 2012.
DOI : 10.1109/EMS.2012.56

P. J. Rousseeuw, Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, Journal of Computational and Applied Mathematics, vol.20, pp.53-65, 1987.
DOI : 10.1016/0377-0427(87)90125-7
URL : https://doi.org/10.1016/0377-0427(87)90125-7

T. A. Runkler, Data Analytics, 2012.

J. Sander, M. Ester, H. P. Kriegel, and X. Xu, Density-based clustering in spatial databases: The algorithm gdbscan and 475 its applications. Data mining and knowledge discovery 2, pp.169-194, 1998.

X. Tang, J. Gu, Z. Shen, and P. Chen, A flight profile clustering method combining twed with K-means algorithm for 4D trajectory prediction, 2015 Integrated Communication, Navigation and Surveillance Conference (ICNS), pp.2015-2018, 2015.
DOI : 10.1109/ICNSURV.2015.7121260

K. Tastambekov, S. Puechmorel, D. Delahaye, and C. Rabut, Aircraft trajectory forecasting using local functional regression 480 in sobolev space. Transportation research part C: emerging technologies 39, pp.1-22, 2014.
DOI : 10.1016/j.trc.2013.11.013

S. Trivedi, Z. A. Pardos, and N. T. Heffernan, The utility of clustering in prediction tasks. arXiv preprint, 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

L. Xi, Z. Jun, Z. Yanbo, and L. Wei, Simulation study of algorithms for aircraft trajectory prediction based on ads-b technology, in: System Simulation and Scientific Computing, Asia Simulation Conference-7th International Conference on, pp.322-327, 2008.