Challenges in Predicting Smart Grid Stability Linked with Renewable Energy Resources Through Spark MLlib Learning
Authors
Amal Zouhri
Sidi Mohammed Ben Abdellah University, Faculty of Sciences Dhar el mahraz, Laboratory of Electronics, Signals, Systems and Computer Science, Fez, Morocco
Ismail Boumhidi
Sidi Mohammed Ben Abdellah University, Faculty of Sciences Dhar el mahraz, Laboratory of Electronics, Signals, Systems and Computer Science, Fez, Morocco
Ismail Boumhidi
Sidi Mohammed Ben Abdellah University, Faculty of Sciences Dhar el mahraz, Laboratory of Electronics, Signals, Systems and Computer Science, Fez, Morocco
Abderahamane Ez-Zahout
Mohammed V University Adjunct Professor at SSE School of Science and Engineering, Al Akhawayn University, Ifrane, Morocco
Said Chakouk
Faculty of Letters and Human Sciences, Mohammed V University in Rabat, Rabat, Morocco
Mostafa El Mallahi
Sidi Mohammed ben Abdellah University, Ecole Normale SupĒrieure, Fez, Morocco
Language: English
Page range: 70 - 81
Submitted on: Apr 28, 2023
Accepted on: Sep 4, 2024
Published on: Dec 24, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
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© 2025 Amal Zouhri, Ismail Boumhidi, Ismail Boumhidi, Abderahamane Ez-Zahout, Said Chakouk, Mostafa El Mallahi, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.