S. Consortium, Milestone Deliverable D3: The ATM Target Concept, 2007.

H. Swenson, R. Barhydt, and M. Landis, Next Generation Air Transportation System (NGATS) Air Traffic Management (ATM)-Airspace Project, National Aeronautics and Space Administration, 2006.

R. Alligier, D. Gianazza, and N. Durand, Ground-based estimation of the aircraft mass, adaptive vs. least squares method, ATM 2013, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00911686

X. Prats, V. Puig, J. Quevedo, and F. Nejjari, Multi-objective optimisation for aircraft departure trajectories minimising noise annoyance, Transportation Research Part C: Emerging Technologies, vol.18, issue.6, pp.975-989, 2010.
DOI : 10.1016/j.trc.2010.03.001

G. Chaloulos, E. Crãijck, and J. Lygeros, A simulation based study of subliminal control for air traffic management, Transportation Research Part C: Emerging Technologies, vol.18, issue.6, pp.963-974, 2010.
DOI : 10.1016/j.trc.2010.03.002

N. Durand, J. M. Alliot, and J. Noailles, Automatic aircraft conflict resolution using genetic algorithms, Proceedings of the 1996 ACM symposium on Applied Computing , SAC '96, 1996.
DOI : 10.1145/331119.331195

URL : https://hal.archives-ouvertes.fr/hal-00937685

F. Drogoul, P. Averty, and R. Weber, Erasmus strategic deconfliction to benefit sesar, Proceedings of the 8th USA, 2009.

B. Musialek, C. F. Munafo, H. Ryan, and M. Paglione, Literature survey of trajectory predictor technology, 2010.

C. Gong and D. Mcnally, A Methodology for Automated Trajectory Prediction Analysis, AIAA Guidance, Navigation, and Control Conference and Exhibit, 2004.
DOI : 10.2514/6.2004-4788

R. A. Vivona, M. M. Paglione, K. T. Cate, and G. Enea, Definition and Demonstration of a Methodology for Validating Aircraft Trajectory Predictors, AIAA Guidance, Navigation, and Control Conference, 2010.
DOI : 10.2514/6.2010-8161

J. Romanelli, C. Santiago, M. Paglione, and A. Schwartz, Climb trajectory prediction software validation for decision support tools and simulation models. International Test and Evaluation Association, 2009.

R. A. Coppenbarger, En route climb trajectory prediction enhancement using airline flight-planning information, Guidance, Navigation, and Control Conference and Exhibit, 1999.
DOI : 10.2514/6.1999-4147

C. Bontemps, Prévision stochastique de trajectoires : procédures paramétriques et non-paramétriques. Master's thesis, 1997.

I. Lymperopoulos, J. Lygeros, and A. L. Visintini, Model Based Aircraft Trajectory Prediction During Takeoff, AIAA Guidance, Navigation, and Control Conference and Exhibit, 2006.
DOI : 10.2514/6.2006-6098

R. Alligier, D. Gianazza, and N. Durand, Energy rate prediction using an equivalent thrust setting profile, 5th International Conference on Research in Air Transportation, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00938734

M. Ghasemi-hamed, M. Serrurier, and N. Durand, Possibilistic knn regression using tolerance intervals, IPMU 2012, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00938763

M. Ghasemi-hamed, M. Serrurier, and N. Durand, Simultaneous Interval Regression for K-Nearest Neighbor, Australasian Conference on Artificial Intelligence, pp.602-613, 2012.
DOI : 10.1007/978-3-642-35101-3_51

URL : https://hal.archives-ouvertes.fr/hal-00938894

W. S. Cleveland and S. J. Devlin, Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting, Journal of the American Statistical Association, vol.41, issue.810345, pp.596-610, 1988.
DOI : 10.1080/01621459.1988.10478639

F. Imado and T. Kinoshita, The application of an uav flight simulator -the development of a new point mass model for an aircraft, SICE-ICASE International Joint Conference Conference, 2006.

A. Nuic, User manual for base of aircarft data (bada) rev.3.7, 2009.

R. Norman, R. Draper, and . Craig-van-nostrand, Ridge regression and james-stein estimation: Review and comments, Technometrics, vol.21, issue.4, pp.451-466, 1979.

R. Tibshirani, Regression shrinkage and selection via the lasso, J. Roy. Stat.Society. Series B (Methodological), vol.58, issue.1, pp.267-288, 1996.

B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, Least angle regression, Ann. Stat, vol.32, issue.2, pp.407-451, 2004.

C. M. Bishop, Neural networks for pattern recognition, pp.0-198, 1996.

B. D. Ripley, Pattern recognition and neural networks, pp.0-521, 1996.
DOI : 10.1017/CBO9780511812651

Y. and L. Fablec, Prévision de trajectoires d'avions par réseaux de neurones, 1999.

R. L. Eubank, Nonparametric Regression and Spline Smoothing, Second Edition Statistics: A Series of Textbooks and Monogrphs, 1999.

T. J. Hastie, R. J. Tibshirani, R. J. Hastie, and . Tibshirani, Generalized Additive Models: T, Chapman and Hall/CRC Monographs on Statistics and Applied Probability Series. Chapman & Hall, 1990.

W. Härdle, Applied nonparametric regression Econometric Society Monographs (No. 19), 1990.

G. Wahba, Spline models for observational data, CBMS- NSF Regional Conference Series in Applied Mathematics. Society for Industrial and Applied Mathematics (SIAM), vol.59, 1990.
DOI : 10.1137/1.9781611970128

J. Fan and I. Gijbels, Local Polynomial Modelling and Its Applications: Monographs on Statistics and Applied Probability 66. Monographs on Statistics and Applied Probability Consistent nonparametric regression, Ann. Stat, vol.66, issue.54, pp.595-620, 1977.
DOI : 10.1007/978-1-4899-3150-4

W. S. Cleveland, Robust Locally Weighted Regression and Smoothing Scatterplots, Journal of the American Statistical Association, vol.39, issue.368, pp.829-836, 1979.
DOI : 10.1214/aos/1176343886

J. Fan, Design-adaptive Nonparametric Regression, Journal of the American Statistical Association, vol.26, issue.420, pp.998-1004, 1992.
DOI : 10.1214/aos/1176343886

J. Fan, Local Linear Regression Smoothers and Their Minimax Efficiencies, The Annals of Statistics, vol.21, issue.1, pp.196-216, 1993.
DOI : 10.1214/aos/1176349022

J. Fan and I. Gijbels, Variable bandwidth and local linear regression smoothers. The Annals of Statistics, pp.2008-2036, 1992.

D. Ruppert and M. P. Wand, Multivariate locally weighted least squares regression. The Annals of Statistics, pp.1346-1370, 1994.

Q. Li and J. S. Racine, Nonparametric econometrics: theory and practice, 2007.

C. G. Atkeson, A. Moore, Y. , S. Schaal, and Z. , Locally Weighted Learning, Artificial Intelligence Review, pp.11-73, 1997.
DOI : 10.1007/978-94-017-2053-3_2

C. R. Rao and H. Toutenburg, Linear Models: Least Squares and Alternatives, 1999.

M. Ghasemi, Hamed currently a PhD student at the MAIAA lab of ENAC. M. Ghasemi Hamed is currently studying regression methods (probabilistic and possibilistic) for the ground based aircraft trajectory prediction problem, 2010.