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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:

Explainable fault diagnosis of oil-gas treatment station based on transfer learning
Jiaquan Liu, Lei Hou, Rui Zhang, et al.
Energy (2022) Vol. 262, pp. 125258-125258
Closed Access | Times Cited: 14

Showing 14 citing articles:

Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery
Shengnan Tang, Jingtao Ma, Zhengqi Yan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108678-108678
Closed Access | Times Cited: 27
Digital twin-assisted dual transfer: a novel information-model adaptation method for rolling bearing fault diagnosis
Zixian Li, Xiaoxi Ding, Zhenzhen Song, et al.
Information Fusion (2024), pp. 102271-102271
Closed Access | Times Cited: 15
Generalization analysis and improvement of CNN-based nuclear power plant fault diagnosis model under varying power levels
Meng Lin, Jiangkuan Li, Yankai Li, et al.
Energy (2023) Vol. 282, pp. 128905-128905
Closed Access | Times Cited: 17
An effective approach for early fuel leakage detection with enhanced explainability
Ruimin Chu, Li Chik, Yiliao Song, et al.
Intelligent Systems with Applications (2025), pp. 200504-200504
Open Access
Fault Diagnosis Across Aircraft Systems Using Image Recognition and Transfer Learning
Lilin Jia, Cordelia Mattuvarkuzhali Ezhilarasu, Ian Jennions
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 3232-3232
Open Access
Deep reinforcement learning based interpretable photovoltaic power prediction framework
Rongquan Zhang, Siqi Bu, Min Zhou, et al.
Sustainable Energy Technologies and Assessments (2024) Vol. 67, pp. 103830-103830
Closed Access | Times Cited: 4
A propagation path-based interpretable neural network model for fault detection and diagnosis in chemical process systems
Benjamin Nguyen, Moncef Chioua
Control Engineering Practice (2024) Vol. 150, pp. 105988-105988
Open Access | Times Cited: 4
Enhancing Reliability Through Interpretability: A Comprehensive Survey of Interpretable Intelligent Fault Diagnosis in Rotating Machinery
Gang Chen, Junlin Yuan, Yiyue Zhang, et al.
IEEE Access (2024) Vol. 12, pp. 103348-103379
Open Access | Times Cited: 3
Toward Production Forecasting for Shale Gas Wells Using Transfer Learning
Wente Niu, Yuping Sun, Xuefeng Yang, et al.
Energy & Fuels (2023) Vol. 37, Iss. 7, pp. 5130-5142
Closed Access | Times Cited: 9
Knowledge sharing-based multi-block federated learning for few-shot oil layer identification
Bingyang Chen, Xingjie Zeng, Weishan Zhang, et al.
Energy (2023) Vol. 283, pp. 128406-128406
Closed Access | Times Cited: 7
Enhancing fault diagnosis of undesirable events in oil & gas systems: A machine learning approach with new criteria for stability analysis and classification accuracy
Mohammed Amine Sahraoui, Chemseddine Rahmoune, Mohamed Zair, et al.
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering (2023)
Open Access | Times Cited: 4
Reservoir properties inversion using attention-based parallel hybrid network integrating feature selection and transfer learning
Jun Wang, Junxing Cao
Energy (2024) Vol. 304, pp. 132069-132069
Closed Access | Times Cited: 1
Fault classification of photovoltaic module infrared images based on transfer learning and interpretable convolutional neural network
Ruoli Tang, Zongyang Ren, Siwen Ning, et al.
Solar Energy (2024) Vol. 276, pp. 112703-112703
Closed Access | Times Cited: 1
Enhancing Trustworthiness in AI-Based Prognostics: A Comprehensive Review of Explainable AI for PHM
Duc An Nguyen, Khanh T.P. Nguyen, Kamal Medjaher
Springer series in reliability engineering (2024), pp. 101-136
Closed Access
Explainable fault diagnosis method for process flow based on data augmentation with system graph relationship
Jiaquan Liu, Lei Hou, Xinru Zhang, et al.
Geoenergy Science and Engineering (2024) Vol. 243, pp. 213334-213334
Closed Access
Transfer Learning for the Prediction of Energy Performance of Water-Cooled Electric Chillers: Grey-Box Models Versus Deep Neural Network (DNN) Models
Hongwen Dou, Radu Zmeureanu
Energies (2024) Vol. 17, Iss. 23, pp. 5981-5981
Open Access
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