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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Ensemble Machine Learning for Predicting the Power Output from Different Solar Photovoltaic Systems
Veena Raj, Sam-Quarcoo Dotse, Sathyajith Mathew, et al.
Energies (2023) Vol. 16, Iss. 2, pp. 671-671
Open Access | Times Cited: 21

Showing 21 citing articles:

Machine learning solutions for renewable energy systems: Applications, challenges, limitations, and future directions
Zaid Allal, Hassan Noura, Ola Salman, et al.
Journal of Environmental Management (2024) Vol. 354, pp. 120392-120392
Closed Access | Times Cited: 28
Forecasting Solar Photovoltaic Power Production: A Comprehensive Review and Innovative Data-Driven Modeling Framework
Sameer Al‐Dahidi, Manoharan Madhiarasan, Loiy Al‐Ghussain, et al.
Energies (2024) Vol. 17, Iss. 16, pp. 4145-4145
Open Access | Times Cited: 14
Hour-Ahead Photovoltaic Power Prediction Combining BiLSTM and Bayesian Optimization Algorithm, with Bootstrap Resampling for Interval Predictions
Reinier Herrera Casanova, Arturo Conde Enrı́quez, Carlos Santos
Sensors (2024) Vol. 24, Iss. 3, pp. 882-882
Open Access | Times Cited: 6
Machine Learning Algorithms in Photovoltaics: Evaluating Accuracy and Computational Cost Across Datasets of Different Generations, Sizes, and Complexities
Omar Al-Saban, Muath Alkadi, Saif M. H. Qaid, et al.
Journal of Electronic Materials (2024) Vol. 53, Iss. 3, pp. 1530-1538
Closed Access | Times Cited: 5
Exploring the landscape of deep learning for solar photovoltaic power output forecasting: A review
Dheeraj Kumar Dhaked, V. L. Narayanan, Ram Gopal, et al.
Renewable energy focus (2025), pp. 100682-100682
Closed Access
Advanced machine learning techniques for predicting power generation and fault detection in solar photovoltaic systems
Montaser Abdelsattar, Ahmed AbdelMoety, Ahmed Emad-Eldeen
Neural Computing and Applications (2025)
Open Access
Application of Machine Learning Models in Social Sciences: Managing Nonlinear Relationships
Theodoros Kyriazos, Mary Poga
Encyclopedia (2024) Vol. 4, Iss. 4, pp. 1790-1805
Open Access | Times Cited: 4
High-Accuracy Photovoltaic Power Prediction under Varying Meteorological Conditions: Enhanced and Improved Beluga Whale Optimization Extreme Learning Machine
Wei Du, Shitao Peng, Peisen Wu, et al.
Energies (2024) Vol. 17, Iss. 10, pp. 2309-2309
Open Access | Times Cited: 3
Assessing Machine Learning Approaches for Photovoltaic Energy Prediction in Sustainable Energy Systems
Montaser Abdelsattar, Mohamed A. Ismeil, Mohamed M. A. Azim Zayed, et al.
IEEE Access (2024) Vol. 12, pp. 107599-107615
Open Access | Times Cited: 3
Recent Trends in Real-Time Photovoltaic Prediction Systems
Isaac Gallardo, Daniel Amor, Álvaro Gutiérrez
Energies (2023) Vol. 16, Iss. 15, pp. 5693-5693
Open Access | Times Cited: 4
Response of Sustainable Solar Photovoltaic Power Output to Summer Heatwave Events in Northern China
Zifan Huang, Zexia Duan, Yichi Zhang, et al.
Sustainability (2024) Vol. 16, Iss. 12, pp. 5254-5254
Open Access | Times Cited: 1
Predictive modeling of photovoltaic system cleaning schedules using machine learning techniques
Haneen Abuzaid, Mahmoud Awad, Abdulrahim Shamayleh, et al.
Renewable Energy (2024) Vol. 239, pp. 122149-122149
Closed Access | Times Cited: 1
Analysis of variables to determine their influence on renewable energy forecasting using ensemble methods
Carlos M. Travieso, Sergio Celada-Bernal, Alejandro Lomoschitz, et al.
Heliyon (2024) Vol. 10, Iss. 9, pp. e30002-e30002
Open Access
The performance comparison of machine learning methods for solar PV power prediction
Funda Demir
World Journal of Engineering (2024)
Closed Access
Establishing Lightweight and Robust Prediction Models for Solar Power Forecasting Using Numerical–Categorical Radial Basis Function Deep Neural Networks
Chee-Hoe Loh, Yi‐Chung Chen, Chwen‐Tzeng Su, et al.
Applied Sciences (2024) Vol. 14, Iss. 22, pp. 10625-10625
Open Access
How Would Different Solar PV Systems Perform Under Tropical Environments?
V Femin, R. Veena, M.I. Petra, et al.
Research Square (Research Square) (2024)
Open Access
Deep Learning Forecasting of Photovoltaics Output Using Digital Twin Data
Nomfundo Vilakazi, Terence L. van Zyl
Communications in computer and information science (2024), pp. 405-419
Closed Access
Energy transition: paving the way for a greener future
Asha Rani N. R., Treshella Laishram, Sasmita Bal
Nanomaterials and Energy (2023) Vol. 12, Iss. 3, pp. 100-109
Closed Access | Times Cited: 1
Solar Power Forecasting using Stacking Ensemble Models with Bayesian Meta-Learning
K. Natarajan, Jai Govind Singh
2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (2023)
Closed Access | Times Cited: 1
Evaluation of Perceptron Learning Algorithm for Day-Ahead Photovoltaic Power Forecasting
Phan Quang An, Christian O’Leary, Gary Smith, et al.
(2023), pp. 255-259
Closed Access
FPGA implementation of KNN Algorithm-Based Prediction for DPWM Methods
T. Anitha P. Jegadeeshwari
Tuijin Jishu/Journal of Propulsion Technology (2023) Vol. 44, Iss. 3, pp. 2455-2464
Open Access
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