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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:

A privacy-preserving framework integrating federated learning and transfer learning for wind power forecasting
Yugui Tang, Shujing Zhang, Zhen Zhang
Energy (2023) Vol. 286, pp. 129639-129639
Closed Access | Times Cited: 13

Showing 13 citing articles:

A Wind and Solar Power Prediction Method Based on Temporal Convolutional Network–Attention–Long Short-Term Memory Transfer Learning and Sensitive Meteorological Features
Yuan Wang, Yue Bi, Guo Yu, et al.
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1636-1636
Open Access
A Three-stage Adjustable Robust Optimization Framework for Energy Base Leveraging Transfer Learning
Yuan Gao, Yucan Zhao, Sile Hu, et al.
Energy (2025), pp. 135037-135037
Closed Access
A dynamic multi-model transfer based short-term load forecasting
Ling Xiao, Qinyi Bai, Binglin Wang
Applied Soft Computing (2024) Vol. 159, pp. 111627-111627
Closed Access | Times Cited: 3
Mutual Knowledge Distillation Based Federated Learning for Short-term Forecasting in Electric IoT Systems
Cheng Tong, Linghua Zhang, Yin Ding, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 19, pp. 31190-31205
Closed Access | Times Cited: 3
A differential privacy-preserving federated learning scheme with predictive maintenance of wind turbines based on deep learning for feature compression and anomaly detection with state assessment
Huan Chen, Hsin-Yao Hsu, Jia‐You Hsieh, et al.
Journal of Mechanical Science and Technology (2024) Vol. 38, Iss. 7, pp. 3413-3429
Closed Access | Times Cited: 2
HFTL-KD: A new heterogeneous federated transfer learning approach for degradation trajectory prediction in large-scale decentralized systems
Shixiang Lü, Zhi-Wei Gao, Yuanhong Liu
Control Engineering Practice (2024) Vol. 153, pp. 106098-106098
Closed Access | Times Cited: 2
A federated transfer learning approach for lithium-ion battery lifespan early prediction considering privacy preservation
Zhen Zhang, Yanyu Wang, X. D. Ruan, et al.
Journal of Energy Storage (2024) Vol. 102, pp. 114153-114153
Closed Access | Times Cited: 1
CFL-ICCV: Clustered federated learning framework with an intra-cluster cross-validation mechanism for DER forecasting
Linbin Liu, June Li, Juan Wang
Applied Energy (2024) Vol. 377, pp. 124699-124699
Closed Access | Times Cited: 1
Federated learning framework for prediction of net energy demand in transactive energy communities
Nuno Mendes, Jérôme Mendes, Javad Mohammadi, et al.
Sustainable Energy Grids and Networks (2024) Vol. 40, pp. 101522-101522
Open Access
Distributed Photovoltaic Power Forecasting Based on Personalized Federated Adversarial Learning
Fang‐Ming Deng, Jinbo Wang, Lei Wu, et al.
Sustainable Energy Grids and Networks (2024), pp. 101537-101537
Closed Access
Lithium-ion batteries lifetime early prediction using domain adversarial learning
Zhen Zhang, Yanyu Wang, X. D. Ruan, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 208, pp. 115035-115035
Closed Access
Probability density function based adaptive ensemble learning with global convergence for wind power prediction
Jianfang Li, Jia Li, Chengyu Zhou
Energy (2024) Vol. 312, pp. 133573-133573
Closed Access
Federated learning and non-federated learning based power forecasting of photovoltaic/wind power energy systems: A systematic review
Filippo Sanfilippo, Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, et al.
Energy and AI (2024) Vol. 18, pp. 100438-100438
Open Access
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