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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 hybrid deep learning model towards fault diagnosis of drilling pump
Junyu Guo, Yulai Yang, He Li, et al.
Applied Energy (2024) Vol. 372, pp. 123773-123773
Open Access | Times Cited: 12

Showing 12 citing articles:

Application of hybrid machine learning algorithm in multi-objective optimization of green building energy efficiency
Yi Zhu, Wen Xu, Wenhong Luo, et al.
Energy (2025), pp. 133581-133581
Closed Access | Times Cited: 4
A hybrid fault diagnosis scheme for milling tools using MWN-CBAM-PatchTST network with acoustic emission signals
Junyu Guo, Hongyun Luo, Yongming Xing, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-29
Closed Access | Times Cited: 1
An Integrated Deep Learning Model for Intelligent Recognition of Long-distance Natural Gas Pipeline Features
Lin Wang, Wannian Guo, Junyu Guo, et al.
Reliability Engineering & System Safety (2024), pp. 110664-110664
Closed Access | Times Cited: 7
Improving active power regulation for wind turbine by phase leading cascaded error-based active disturbance rejection control and multi-objective optimization
Xuehan Li, Wei Wang, Fang Fang, et al.
Renewable Energy (2025) Vol. 243, pp. 122629-122629
Closed Access
A hybrid deep learning model towards flow pattern identification of gas-liquid two-phase flows in horizontal pipe
Tingxia Ma, Tianxin Wang, Lin Wang, et al.
Energy (2025), pp. 135141-135141
Closed Access
Multi-label learning for fault diagnosis of pumping units with one positive label
Kun Qian, Jinyu Tang, Qiulin Zhao, et al.
Applied Soft Computing (2025), pp. 113014-113014
Closed Access
Deep Learning-Based Fatigue Strength Prediction for Ferrous Alloy
Zhikun Huang, Jingchao Yan, Jianlong Zhang, et al.
Processes (2024) Vol. 12, Iss. 10, pp. 2214-2214
Open Access | Times Cited: 3
Data-Driven Feature Extraction-Transformer: A Hybrid Fault Diagnosis Scheme Utilizing Acoustic Emission Signals
Chenggong Ma, Jiuyang Gao, Zhenggang Wang, et al.
Processes (2024) Vol. 12, Iss. 10, pp. 2094-2094
Open Access | Times Cited: 2
TSViT: A Time Series Vision Transformer for Fault Diagnosis of Rotating Machinery
Shouhua Zhang, Jiehan Zhou, Xue Ma, et al.
Applied Sciences (2024) Vol. 14, Iss. 23, pp. 10781-10781
Open Access | Times Cited: 1
Improving Electrical Fault Detection Using Multiple Classifier Systems
José Gerardo Beserra de Oliveira, Dioéliton Passos, Davi Carvalho, et al.
Energies (2024) Vol. 17, Iss. 22, pp. 5787-5787
Open Access
A random effects Wiener process model with acceleration factors for remaining useful life prediction
Yongqiang Yang, Quan Zou, Junyu Guo, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 12
Closed Access
A Parallel Prognostic Method Integrating Uncertainty Quantification for Probabilistic Remaining Useful Life Prediction of Aero-Engine
Rongqiu Wang, Ya Zhang, Chen Hu, et al.
Processes (2024) Vol. 12, Iss. 12, pp. 2925-2925
Open Access
Drilling Bit Wear Monitoring Method Based on Multi-Head Attention Mechanism and Hybrid Neural Networks
Shibo Fang, Hualin Liao, Jiansheng Liu, et al.
Geoenergy Science and Engineering (2024), pp. 213635-213635
Closed Access
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