Rushdi, M.A.; Rushdi, A.A.; Dief, T.N.; Halawa, A.M.; Yoshida, S.; Schmehl, R.
Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning. Energies 2020, 13, 2367.
https://doi.org/10.3390/en13092367
AMA Style
Rushdi MA, Rushdi AA, Dief TN, Halawa AM, Yoshida S, Schmehl R.
Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning. Energies. 2020; 13(9):2367.
https://doi.org/10.3390/en13092367
Chicago/Turabian Style
Rushdi, Mostafa A., Ahmad A. Rushdi, Tarek N. Dief, Amr M. Halawa, Shigeo Yoshida, and Roland Schmehl.
2020. "Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning" Energies 13, no. 9: 2367.
https://doi.org/10.3390/en13092367
APA Style
Rushdi, M. A., Rushdi, A. A., Dief, T. N., Halawa, A. M., Yoshida, S., & Schmehl, R.
(2020). Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning. Energies, 13(9), 2367.
https://doi.org/10.3390/en13092367