1. Abascal, A.J., Castanedo, S., Minguez, R., Medina, R., Liu, Y., Weisberg, R.H., 2015. Stochastic Lagrangian trajectory modeling of surface drifters deployed during the Deepwater Horizon oil spill. In: Proceedings of the Thirty-Eighth AMOP Technical Seminar; Environment Canada: Ottawa, on, Canada. pp. 77–91.
2. Long-term wind speed and power forecasting using local recurrent neural network models;Barbounis;IEEE Trans. Energy Convers.,2006
3. The oil spill model OILTRANS and its application to the Celtic Sea;Berry;Mar. Pollut. Bull.,2012
4. AWNN-assisted wind power forecasting using feed-forward neural network;Bhaskar;IEEE Trans. Sustain. Energy,2012
5. Integrated analysis of multisensor datasets and oil drift simulations—A free-floating oil experiment in the open ocean;Brekke;J. Geophys. Res. Oceans,2021