Ensemble Learning Algorithms for Solar Power Prediction in Saudi Arabia: A Data-Driven Approach-Reference-Cited by-同舟云学术

Ensemble Learning Algorithms for Solar Power Prediction in Saudi Arabia: A Data-Driven Approach

Published:2024-01-28 Issue: Volume: Page:
ISSN:
Container-title:2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)
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Author:

Hossain Mohammad Kamal¹,Arifuzzaman Md²,Seliaman Mohamed Elhasan³,Rahman Arifur⁴,Sarker Debasish⁵,Altammar Hussain⁶

Affiliation:

1. Interdisciplinary Research Center for Sustainable Energy System (IRC-SES), King Fahd University of Petroleum and Minerals (KFUPM),Dhahran,Saudi Arabia,31261

2. Civil and Environmental Engineering, King Faisal University,Al Hafuf,Saudi Arabia

3. King Faisal University,Department of Information Systems,Al Hafuf,Saudi Arabia

4. Mechanical Engineering, King Fahd University of Petroleum and Minerals (KFUPM),Dhahran,Saudi Arabia,31261

5. Mechanical Engineering College of Engineering and Technology, International University of Business Agriculture and Technology,Bangladesh

6. Mechanical Engineering, King Faisal University,Al Hafuf,Saudi Arabia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10459226/10459347/10459648.pdf?arnumber=10459648

Reference10 articles.

1. Saudi Arabia has become a key hub for green energy,2023

2. A model tree approach to forecasting solar irradiance variability

3. Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning

4. Wind power prediction using bootstrap aggregating trees approach to enabling sustainable wind power integration in a smart grid

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