Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Power Forecasting of Regional Wind Farms via Variational Auto-Encoder and Deep Hybrid Transfer Learning
Mansoor Khan, Muhammad Rashid Naeem, Essam A. Al‐Ammar, et al.
Electronics (2022) Vol. 11, Iss. 2, pp. 206-206
Open Access | Times Cited: 20

Showing 20 citing articles:

Opportunities for Early Detection and Prediction of Ransomware Attacks against Industrial Control Systems
Mazen Gazzan, Frederick T. Sheldon
Future Internet (2023) Vol. 15, Iss. 4, pp. 144-144
Open Access | Times Cited: 25
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: 9
Enhancing wind power forecasting accuracy through LSTM with adaptive wind speed calibration (C-LSTM)
Ding Wang, Min Xu, Guangming Zhu, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Prediction of regional wind power generation using a multi-objective optimized deep learning model with temporal pattern attention
Wenhe Chen, Hanting Zhou, Longsheng Cheng, et al.
Energy (2023) Vol. 278, pp. 127942-127942
Closed Access | Times Cited: 22
Model selection, adaptation, and combination for transfer learning in wind and photovoltaic power forecasts
Jens Schreiber, Bernhard Sick
Energy and AI (2023) Vol. 14, pp. 100249-100249
Open Access | Times Cited: 16
Transfer Learning for Renewable Energy Systems: A Survey
Rami Al-Hajj, Ali Assi, Bilel Neji, et al.
Sustainability (2023) Vol. 15, Iss. 11, pp. 9131-9131
Open Access | Times Cited: 14
A wind power smoothing control strategy using energy storage systems under extreme weather conditions based on IKELM-MPC
Hao Liu, Qingqing Xu, Xuan Zhang, et al.
Journal of Energy Storage (2025) Vol. 116, pp. 115872-115872
Closed Access
Synergistic Artificial Intelligence framework for robust multivariate medium-term wind power prediction with uncertainty envelopes
Bo Wu, Xiuli Wang, Bangyan Wang, et al.
Energy and AI (2025), pp. 100513-100513
Open Access
Statistical Foundations of Generative AI for Optimal Control Problems in Power Systems: Comprehensive Review and Future Directions
Elinor Ginzburg-Ganz, Eden Dina Horodi, Omar Shadafny, et al.
Energies (2025) Vol. 18, Iss. 10, pp. 2461-2461
Open Access
Deep neural networks for the quantile estimation of regional renewable energy production
António Alcántara, Inés M. Galván, Ricardo Aler
Applied Intelligence (2022) Vol. 53, Iss. 7, pp. 8318-8353
Open Access | Times Cited: 16
Numerical Simulation of Terrain-Adaptive Wind Field Model Under Complex Terrain Conditions
Xiangqian Wei, Yi Liu, Xinyu Chang, et al.
Water (2024) Vol. 16, Iss. 15, pp. 2138-2138
Open Access | Times Cited: 2
A Review of Deep Transfer Learning Strategy for Energy Forecasting
S. Sankari, P. Senthil Kumar
Nature Environment and Pollution Technology (2023) Vol. 22, Iss. 4, pp. 1781-1793
Open Access | Times Cited: 4
A novel spatial–temporal generative autoencoder for wind speed uncertainty forecasting
Long Ma, Ling Huang, Huifeng Shi
Energy (2023) Vol. 282, pp. 128946-128946
Closed Access | Times Cited: 3
Multi-Task Autoencoders and Transfer Learning for Day-Ahead Wind and Photovoltaic Power Forecasts
Jens Schreiber, Bernhard Sick
Energies (2022) Vol. 15, Iss. 21, pp. 8062-8062
Open Access | Times Cited: 4
Modeling of the Crystallization Conditions for Organic Synthesis Product Purification Using Deep Learning
Mantas Vaškevičius, Jurgita Kapočiūtė-Dzikienė, Liudas Šlepikas
Electronics (2022) Vol. 11, Iss. 9, pp. 1360-1360
Open Access | Times Cited: 3
Multi-Task Representation Learning for Renewable-Power Forecasting: A Comparative Analysis of Unified Autoencoder Variants and Task-Embedding Dimensions
Chandana Priya Nivarthi, S. Vogt, Bernhard Sick
Machine Learning and Knowledge Extraction (2023) Vol. 5, Iss. 3, pp. 1214-1233
Open Access | Times Cited: 1
A novel multi-task transfer model to realize unsupervised fault diagnosis of newly constructed wind turbines under variable conditions
X L Liu, Desheng Sha, Qing Zhang, et al.
(2024), pp. 106-106
Closed Access
Robust Short-Term Wind Power Forecasting Using a Multivariate Input and Hybrid Architecture
Truc Thi Kim Nguyen, Duy Nhu Nhat, Hoang Nhu Thanh Vo, et al.
(2023), pp. 1-6
Closed Access
Renewable Energy Forecast Considering Plateau Mountain and Ocean Climate Characteristics
Weisi Deng, Zhongfu Dai, Haohuai Wang, et al.
2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2) (2023), pp. 3451-3457
Closed Access
Initial considerations
Corinna Möhrlen, John W. Zack, Gregor Giebel
Elsevier eBooks (2022), pp. 83-87
Open Access
Bibliography

Elsevier eBooks (2022), pp. 331-341
Open Access
Page 1

Scroll to top