115
Cornel Stander., (2015). « Analysis of Extreme Events in the Coastal Engineering
Environment », s. d., 147p.
Den Bieman. J. P., van Gent, M. R. A. et al., (2021) ''Wave Overtopping Predictions Using an
Advanced Machine Learning Technique '', Coastal Engineering 166: 103830. Disponible sur le
web : https://doi.org/10.1016/j.coastaleng.2020.103830, 12p.
DHI., (2014). MIKE 21/3 Couple Model FM.
DHI., (2014). MIKE 21 Spectral Wave Module.
DHI., (2014). MIKE ZERO: Creating 2D Bathymetries. Bathymetry Editor & Mesh Generator.
Goethals. I., Pelckmans. K. et al., (2005). Subspace Identification of Hammerstein Systems using
Least Squares Support Vector Machines. IEEE Trans. on Automatic Control 50, 1519p.
Gosse Jan Steendam, (2004), '' The international data base on wave overtopping '', in Coastal
Engineering 2004 (Proceedings of the 29th International Conference, National Civil Engineering
Laboratory, Lisbon, Portugal: World Scientific Publishing Company), 4301‑13. Disponible sur le
web : https://doi.org/10.1142/9789812701916_0347, 15p.
H. Verhaeghe ., J. W. van der Meer. et al., (2003). Wave overtopping database as the starting
point for a neural network prediction method. ASCE, Proc. Coastal Structures 2003, Portland, 430
p.
H. O. Pörtner., D. C. Roberts. et al., (2022), ''The Ocean and Cryosphere in a Changing Climate:
Special Report of the Intergovernmental Panel on Climate Change'', IPCC, 1re éd. (Cambridge
University Press,), https://doi.org/10.1017/9781009157964, 40p.
Janecek., (2007),’Computational Neuroscience, Artificial Neural Network’. [En ligne]. [Consulté
le 16/05/2022]. Disponible sur le web : https://www.scribd.com/document/326923737/2007-0201bJanecek-Perceptron.
Jungkyu.A., Yeji.N., Sung. W.P., (2019) « Development of Two-Dimensional Inundation
Modelling Process Using MIKE21 Model », KSCE Journal of Civil Engineering 23, no 9:
3968‑77, https://doi.org/10.1007/s12205-019-1586-9, 58p.
Laboratoire 2 ETS. (2012), ‘Entraînement et évaluation d’une méthode de régression’
Département de génie logiciel et desti LOG770 systèmes intelligent. Internet : Laboratoire 2
ETS.08p.
M.R.A. Van Gent., B. Pozueta. et al., (2005). Prediction method Neural network modelling of
wave overtopping at coastal structures. WL, delft hydraulics. Commission of the European
Communities, CLASH (EVK3-2001-00058).33p.
Mohamadally. H., Fomani. B., (2006) ’ SVM : Machines à Vecteurs de Support ou Séparateurs
à Vastes Marges’, s. d., 20.BD Web, ISTY3. Versailles St Quentin, France. 20p.
Nassim Laouti., (2012), 'Diagnostic de défauts par les Machines à Vecteurs Supports : application
à différents systèmes multivariables non linéaires', s. d., 271. Université Claude Bernard - Lyon I,
Français. FfNNT : 2012LYO10161ff. Fftel-00985437f, 271p.
Pozueta. B., M. R. Van Gent. et al., (2005), "Neural network modelling of wave overtopping at
coastal structures." In Coastal Engineering 2004: (In 4 Volumes), 4287p.
Cornel Stander., (2015). « Analysis of Extreme Events in the Coastal Engineering
Environment », s. d., 147p.
Den Bieman. J. P., van Gent, M. R. A. et al., (2021) ''Wave Overtopping Predictions Using an
Advanced Machine Learning Technique '', Coastal Engineering 166: 103830. Disponible sur le
web : https://doi.org/10.1016/j.coastaleng.2020.103830, 12p.
DHI., (2014). MIKE 21/3 Couple Model FM.
DHI., (2014). MIKE 21 Spectral Wave Module.
DHI., (2014). MIKE ZERO: Creating 2D Bathymetries. Bathymetry Editor & Mesh Generator.
Goethals. I., Pelckmans. K. et al., (2005). Subspace Identification of Hammerstein Systems using
Least Squares Support Vector Machines. IEEE Trans. on Automatic Control 50, 1519p.
Gosse Jan Steendam, (2004), '' The international data base on wave overtopping '', in Coastal
Engineering 2004 (Proceedings of the 29th International Conference, National Civil Engineering
Laboratory, Lisbon, Portugal: World Scientific Publishing Company), 4301‑13. Disponible sur le
web : https://doi.org/10.1142/9789812701916_0347, 15p.
H. Verhaeghe ., J. W. van der Meer. et al., (2003). Wave overtopping database as the starting
point for a neural network prediction method. ASCE, Proc. Coastal Structures 2003, Portland, 430
p.
H. O. Pörtner., D. C. Roberts. et al., (2022), ''The Ocean and Cryosphere in a Changing Climate:
Special Report of the Intergovernmental Panel on Climate Change'', IPCC, 1re éd. (Cambridge
University Press,), https://doi.org/10.1017/9781009157964, 40p.
Janecek., (2007),’Computational Neuroscience, Artificial Neural Network’. [En ligne]. [Consulté
le 16/05/2022]. Disponible sur le web : https://www.scribd.com/document/326923737/2007-0201bJanecek-Perceptron.
Jungkyu.A., Yeji.N., Sung. W.P., (2019) « Development of Two-Dimensional Inundation
Modelling Process Using MIKE21 Model », KSCE Journal of Civil Engineering 23, no 9:
3968‑77, https://doi.org/10.1007/s12205-019-1586-9, 58p.
Laboratoire 2 ETS. (2012), ‘Entraînement et évaluation d’une méthode de régression’
Département de génie logiciel et desti LOG770 systèmes intelligent. Internet : Laboratoire 2
ETS.08p.
M.R.A. Van Gent., B. Pozueta. et al., (2005). Prediction method Neural network modelling of
wave overtopping at coastal structures. WL, delft hydraulics. Commission of the European
Communities, CLASH (EVK3-2001-00058).33p.
Mohamadally. H., Fomani. B., (2006) ’ SVM : Machines à Vecteurs de Support ou Séparateurs
à Vastes Marges’, s. d., 20.BD Web, ISTY3. Versailles St Quentin, France. 20p.
Nassim Laouti., (2012), 'Diagnostic de défauts par les Machines à Vecteurs Supports : application
à différents systèmes multivariables non linéaires', s. d., 271. Université Claude Bernard - Lyon I,
Français. FfNNT : 2012LYO10161ff. Fftel-00985437f, 271p.
Pozueta. B., M. R. Van Gent. et al., (2005), "Neural network modelling of wave overtopping at
coastal structures." In Coastal Engineering 2004: (In 4 Volumes), 4287p.