G. Box and G. Jenkins, Time Series Analysis, Forecasting and Control, 1976.

L. E. Christiansen, H. A. Nielsen, T. S. Nielsen, and H. Madsen, Unbounded optimization of variable forgetting factor rls. submitted, 2006.

G. Giebel, J. Badger, I. M. Perez, P. Louka, G. Kallos et al., Shortterm forecasting using advanced physical modelling -the results of the anemos project, Proceedings of the European Wind Energy Conference, 2006.

G. Giebel, R. Brownsword, and G. Kariniotakis, The state-of-the-art in short-term prediction of wind power; a literature overview Evaluation of the morecare wind power prediction platform. performance of the fuzzy logic based models, Proc. of the, 2003.

L. Landberg, G. Giebel, H. A. Nielsen, T. Nielsen, and H. Madsen, Short-term Prediction?An Overview, Wind Energy, vol.14, issue.3, pp.273-280, 2003.
DOI : 10.1002/we.96

M. Lange, On the uncertainty of wind power predictions, 2003.

M. Lange and D. Heinemann, Relating the uncertainty of short-term wind speed predictions to meteorological situations with methods from synoptic climatology, Proceedings of the European Wind Energy Conference & Exhibition, 2003.

P. Louka, G. Galanis, N. S. , G. K. Katsafados, P. Kallos et al., and Pytharoulis I. Improvements in wind speed forecasts for wind power prediction purposes using kalman filtering, Proc. of the 5th Conference on Mathematical Models in Science and Engineering, 2005.

H. Madsen, P. Pinson, G. Kariniotakis, H. A. Nielsen, and T. S. Nielsen, Standardizing the performance evaluation of short-term wind prediction models. Wind Engineering, 2006.

I. Marti, T. Nielsen, H. Madsen, J. Navarro, A. Roldán et al., Prediction models in complex terrain, European Wind Energy Conference . EWEC'01, 2001.

H. Nielsen, H. Madsen, T. Nielsen, J. Badger, G. Giebel et al., Wind power ensemble forecasting, Proceedings of the 2004 Global Windpower Conference and Exhibition, 2004.
URL : https://hal.archives-ouvertes.fr/hal-00812349

H. A. Nielsen and H. Madsen, Wind power prediction using ARX models and neural networks, Proceedings of the Fifteenth IASTED International Conference on Modelling, Identification and Control, pp.310-313, 1996.

H. A. Nielsen, H. Madsen, and T. S. Nielsen, Using quantile regression to extend an existing wind power forecasting system with probabilistic forecasts, Wind Energy, vol.83, issue.1-2, pp.95-108, 2006.
DOI : 10.1002/we.180

H. A. Nielsen, T. S. Nielsen, A. K. Joensen, H. Madsen, and J. Holst, Tracking time-varying-coefficient functions, International Journal of Adaptive Control and Signal Processing, vol.36, issue.8, pp.813-828, 2000.
DOI : 10.1002/1099-1115(200012)14:8<813::AID-ACS622>3.0.CO;2-6

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.44.5943

T. S. Nielsen, H. A. Nielsen, and H. Madsen, Prediction of wind power using time-varying coefficientfunctions, Proceedings of the XV IFAC World Congress, 2002.

P. Pinson, Estimation of the uncertainty in wind power forecasting, 2006.
URL : https://hal.archives-ouvertes.fr/pastel-00002187

P. Pinson and G. Kariniotakis, On-line assessment of prediction risk for wind power production forecasts, Proceedings of the European Wind Energy Conference & Exhibition, 2003.
DOI : 10.1002/we.114

P. Pinson and G. Kariniotakis, On-line adaptation of confidence intervals based on weather stability for wind power forecasting, Proceedings of the Global Wind Energy Conference & Exhibition, 2004.
URL : https://hal.archives-ouvertes.fr/hal-00529488

P. Pinson, N. Siebert, and G. Kariniotakis, Forecasting of regional wind generation by a dynamic fuzzyneural network based upscaling approach, Proc. of the European Wind Energy Conference, 2003.

I. Sanchez, Short-term prediction of wind energy production, International Journal of Forecasting, vol.22, issue.1, pp.43-56, 2006.
DOI : 10.1016/j.ijforecast.2005.05.003

N. Siebert and G. Kariniotakis, Reference wind farm selection for regional wind power prediction models, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00526690