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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:

An intelligent online fault diagnosis system for gas turbine sensors based on unsupervised learning method LOF and KELM
Kanru Cheng, Yuzhang Wang, Xilian Yang, et al.
Sensors and Actuators A Physical (2023) Vol. 365, pp. 114872-114872
Closed Access | Times Cited: 12

Showing 12 citing articles:

Neural Network System for Predicting Anomalous Data in Applied Sensor Systems
Serhii Vladov, Victoria Vysotska, Валерій Сокуренко, et al.
Applied System Innovation (2024) Vol. 7, Iss. 5, pp. 88-88
Open Access | Times Cited: 6
Deep transfer learning strategy in intelligent fault diagnosis of gas turbines based on the Koopman operator
Fatemeh Negar Irani, Mohammadjavad Soleimani, Meysam Yadegar, et al.
Applied Energy (2024) Vol. 365, pp. 123256-123256
Closed Access | Times Cited: 5
Research on intelligent substation secondary system fault diagnosis system based on fuzzy comprehensive judgment
Hongtao Zhang, Ruohan Wang, Gang Zou, et al.
Journal of Physics Conference Series (2025) Vol. 2935, Iss. 1, pp. 012010-012010
Open Access
Helicopter Turboshaft Engines’ Neural Network System for Monitoring Sensor Failures
Serhii Vladov, Łukasz Ścisło, Nina Szczepanik-Ścisło, et al.
Sensors (2025) Vol. 25, Iss. 4, pp. 990-990
Open Access
Research on gas turbine health assessment method based on physical prior knowledge and spatial-temporal graph neural network
Kanru Cheng, Kunyu Zhang, Yuzhang Wang, et al.
Applied Energy (2024) Vol. 367, pp. 123419-123419
Closed Access | Times Cited: 4
Helicopters Turboshaft Engines Neural Network Modeling under Sensor Failure
Serhii Vladov, Anatoliy Sachenko, Валерій Сокуренко, et al.
Journal of Sensor and Actuator Networks (2024) Vol. 13, Iss. 5, pp. 66-66
Open Access | Times Cited: 4
Power transformer fault diagnosis using dynamic multiscale graph modeling and M2SGCN network based on statistical fusion
Xiaoyan Liu, Y. He
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 066009-066009
Closed Access | Times Cited: 3
Advancing predictive maintenance for gas turbines: An intelligent monitoring approach with ANFIS, LSTM, and reliability analysis
Larbi Brahimi, Nadji Hadroug, Abdelhamid Iratni, et al.
Computers & Industrial Engineering (2024) Vol. 191, pp. 110094-110094
Closed Access | Times Cited: 1
Developing machine learning-based ground motion models to predict peak ground velocity in Turkiye
Fahrettin Kuran, Gülüm Tanırcan, Elham Pashaei
Journal of Seismology (2024)
Closed Access | Times Cited: 1
An automatic and efficient fault diagnosis strategy for air conditioning units by combining attention mechanisms
Zhen Jia, Jian G. Qin, Qiqi Yang, et al.
Science and Technology for the Built Environment (2024), pp. 1-11
Closed Access
Data-driven approach for the classification of gas turbine faults
Messaoud Bouakkaz, Hichem Bouras, Nadir Fenghour
STUDIES IN ENGINEERING AND EXACT SCIENCES (2024) Vol. 5, Iss. 2, pp. e11460-e11460
Closed Access
Gas turbine thrust estimation in sensor drift scenarios using a three-stage multi-target domain adaptation method
Hang Zhao, Xiongfei Zhai, Zengbu Liao, et al.
Energy (2024) Vol. 314, pp. 134104-134104
Closed Access
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