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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:

Short-Term Forecasting of Photovoltaic Solar Power Production Using Variational Auto-Encoder Driven Deep Learning Approach
Abdelkader Dairi, Fouzi Harrou, Ying Sun, et al.
Applied Sciences (2020) Vol. 10, Iss. 23, pp. 8400-8400
Open Access | Times Cited: 98

Showing 1-25 of 98 citing articles:

Improved solar photovoltaic energy generation forecast using deep learning-based ensemble stacking approach
Waqas Khan, Shalika Walker, Wim Zeiler
Energy (2021) Vol. 240, pp. 122812-122812
Open Access | Times Cited: 210
Load Forecasting Techniques for Power System: Research Challenges and Survey
Naqash Ahmad, Yazeed Yasin Ghadi, Muhammad Adnan, et al.
IEEE Access (2022) Vol. 10, pp. 71054-71090
Open Access | Times Cited: 134
Forecasting Renewable Energy Generation with Machine Learning and Deep Learning: Current Advances and Future Prospects
Natei Ermias Benti, Mesfin Diro Chaka, Addisu Gezahegn Semie
Sustainability (2023) Vol. 15, Iss. 9, pp. 7087-7087
Open Access | Times Cited: 85
Short-Term Solar Power Predicting Model Based on Multi-Step CNN Stacked LSTM Technique
Neethu Elizabeth Michael, Manohar Mishra, Shazia Hasan, et al.
Energies (2022) Vol. 15, Iss. 6, pp. 2150-2150
Open Access | Times Cited: 77
Short-term PV power forecasting using variational mode decomposition integrated with Ant colony optimization and neural network
Solomon Netsanet, Dehua Zheng, Wei Zhang, et al.
Energy Reports (2022) Vol. 8, pp. 2022-2035
Open Access | Times Cited: 75
A novel method based on time series ensemble model for hourly photovoltaic power prediction
Zenan Xiao, Xiaoqiao Huang, Jun Liu, et al.
Energy (2023) Vol. 276, pp. 127542-127542
Closed Access | Times Cited: 44
An analysis of case studies for advancing photovoltaic power forecasting through multi-scale fusion techniques
Mawloud Guermoui, Amor Fezzani, Zaiani Mohamed, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 27
Enhancing road traffic flow prediction with improved deep learning using wavelet transforms
Fouzi Harrou, Abdelhafid Zeroual, Farid Kadri, et al.
Results in Engineering (2024) Vol. 23, pp. 102342-102342
Open Access | Times Cited: 19
PV-Net: An innovative deep learning approach for efficient forecasting of short-term photovoltaic energy production
Mohamed Abdel‐Basset, Hossam Hawash, Ripon K. Chakrabortty, et al.
Journal of Cleaner Production (2021) Vol. 303, pp. 127037-127037
Closed Access | Times Cited: 93
A hybrid deep learning method for an hour ahead power output forecasting of three different photovoltaic systems
Muhammad Naveed Akhter, Saad Mekhilef, Hazlie Mokhlis, et al.
Applied Energy (2021) Vol. 307, pp. 118185-118185
Closed Access | Times Cited: 91
Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects
Majdi Mansouri, Mohamed Trabelsi, Hazem Nounou, et al.
IEEE Access (2021) Vol. 9, pp. 126286-126306
Open Access | Times Cited: 88
Integrated Multiple Directed Attention-Based Deep Learning for Improved Air Pollution Forecasting
Abdelkader Dairi, Fouzi Harrou, Sofiane Khadraoui, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-15
Closed Access | Times Cited: 72
A deep generative model for probabilistic energy forecasting in power systems: normalizing flows
Jonathan Dumas, Antoine Wehenkel, Damien Lanaspeze, et al.
Applied Energy (2021) Vol. 305, pp. 117871-117871
Open Access | Times Cited: 70
Completed Review of Various Solar Power Forecasting Techniques Considering Different Viewpoints
Yuan‐Kang Wu, Cheng‐Liang Huang, Quoc‐Thang Phan, et al.
Energies (2022) Vol. 15, Iss. 9, pp. 3320-3320
Open Access | Times Cited: 58
Comparative Performance Analysis of PV Module Positions in a Solar PV Array Under Partial Shading Conditions
Hicham Oufettoul, Najwa Lamdihine, Saad Motahhir, et al.
IEEE Access (2023) Vol. 11, pp. 12176-12194
Open Access | Times Cited: 37
A Review for Green Energy Machine Learning and AI Services
Yukta Mehta, Rui Xu, Benjamin Lim, et al.
Energies (2023) Vol. 16, Iss. 15, pp. 5718-5718
Open Access | Times Cited: 23
Semi-supervised Deep Learning-Driven Anomaly Detection Schemes for Cyber-Attack Detection in Smart Grids
Abdelkader Dairi, Fouzi Harrou, Benamar Bouyeddou, et al.
Power systems (2023), pp. 265-295
Closed Access | Times Cited: 22
Efficient solar power generation forecasting for greenhouses: A hybrid deep learning approach
Divyadharshini Venkateswaran, Yongyun Cho
Alexandria Engineering Journal (2024) Vol. 91, pp. 222-236
Open Access | Times Cited: 15
Enhancing wind power prediction with self-attentive variational autoencoders: A comparative study
Fouzi Harrou, Abdelkader Dairi, Abdelhakim Dorbane, et al.
Results in Engineering (2024) Vol. 23, pp. 102504-102504
Open Access | Times Cited: 8
A Comprehensive Survey on Load Forecasting Hybrid Models: Navigating the Futuristic Demand Response Patterns through Experts and Intelligent Systems
Kinza Fida, Usman Abbasi, Muhammad Adnan, et al.
Results in Engineering (2024) Vol. 23, pp. 102773-102773
Open Access | Times Cited: 8
Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review
Mohamed Massaoudi, Inès Chihi, Haitham Abu‐Rub, et al.
IEEE Access (2021) Vol. 9, pp. 136593-136615
Open Access | Times Cited: 50
A hybrid machine learning method with explicit time encoding for improved Malaysian photovoltaic power prediction
Hamza Mubarak, Ahmad Hammoudeh, Shameem Ahmad, et al.
Journal of Cleaner Production (2022) Vol. 382, pp. 134979-134979
Open Access | Times Cited: 36
Forecasting Renewable Energy Generation with Machine learning and Deep Learning: Current Advances and Future Prospects
Natei Ermias Benti, Mesfin Diro Chaka, Addisu Gezahegn Semie
(2023)
Open Access | Times Cited: 21
Predictive evaluation of solar energy variables for a large-scale solar power plant based on triple deep learning forecast models
Irfan Jamil, Lucheng Hong, Sheeraz Iqbal, et al.
Alexandria Engineering Journal (2023) Vol. 76, pp. 51-73
Open Access | Times Cited: 19
A robust regressor model for estimating solar radiation using an ensemble stacking approach based on machine learning
Rahul Gupta, Anil Kumar Yadav, SK Jha, et al.
International Journal of Green Energy (2023) Vol. 21, Iss. 8, pp. 1853-1873
Closed Access | Times Cited: 17
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