Raza, M.A.; Karim, A.; Alqarni, M.; Al-Khasawneh, M.A.; Jumani, T.A.; Aman, M.; Masud, M.I.
An Intelligent Long Short-Term Memory-Based Machine Learning Model for the Potential Assessment of Global Hydropower Capacity in Sustainable Energy Transition and Security. Energies 2025, 18, 3324.
https://doi.org/10.3390/en18133324
AMA Style
Raza MA, Karim A, Alqarni M, Al-Khasawneh MA, Jumani TA, Aman M, Masud MI.
An Intelligent Long Short-Term Memory-Based Machine Learning Model for the Potential Assessment of Global Hydropower Capacity in Sustainable Energy Transition and Security. Energies. 2025; 18(13):3324.
https://doi.org/10.3390/en18133324
Chicago/Turabian Style
Raza, Muhammad Amir, Abdul Karim, Mohammed Alqarni, Mahmoud Ahmad Al-Khasawneh, Touqeer Ahmed Jumani, Mohammed Aman, and Muhammad I. Masud.
2025. "An Intelligent Long Short-Term Memory-Based Machine Learning Model for the Potential Assessment of Global Hydropower Capacity in Sustainable Energy Transition and Security" Energies 18, no. 13: 3324.
https://doi.org/10.3390/en18133324
APA Style
Raza, M. A., Karim, A., Alqarni, M., Al-Khasawneh, M. A., Jumani, T. A., Aman, M., & Masud, M. I.
(2025). An Intelligent Long Short-Term Memory-Based Machine Learning Model for the Potential Assessment of Global Hydropower Capacity in Sustainable Energy Transition and Security. Energies, 18(13), 3324.
https://doi.org/10.3390/en18133324
