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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:

GASEL: Genetic algorithm-supported ensemble learning for fault detection in autonomous underwater vehicles
Duygu Bağcı Daş, Derya Birant
Ocean Engineering (2023) Vol. 272, pp. 113844-113844
Closed Access | Times Cited: 13

Showing 13 citing articles:

Machine learning for fault analysis in rotating machinery: A comprehensive review
Oğuzhan Daş, Duygu Bağcı Daş, Derya Birant
Heliyon (2023) Vol. 9, Iss. 6, pp. e17584-e17584
Open Access | Times Cited: 30
Physics-Guided Generative Adversarial Networks for fault detection of underwater thruster
Shuang Gao, Jixin Liu, Zhiyao Zhang, et al.
Ocean Engineering (2023) Vol. 286, pp. 115585-115585
Closed Access | Times Cited: 17
IPORF: A combined improved parrot optimizer algorithm and random forest for fault diagnosis in AUV
Kangzheng Huang, Wei Bo Li, Fang Hualiang, et al.
Ocean Engineering (2024) Vol. 313, pp. 119665-119665
Closed Access | Times Cited: 7
Physical model embedding-based generative adversarial networks for unsupervised fault detection of underwater thrusters
Shuang Gao, Ze Yu, Zhiyao Zhang, et al.
Ocean Engineering (2024) Vol. 298, pp. 117190-117190
Closed Access | Times Cited: 5
NARX modeling and simulation of heave dynamics with application of robust control of an underactuated underwater vehicle
S.M. Ahmad, Ahsan Tanveer
Ocean Engineering (2025) Vol. 325, pp. 120790-120790
Closed Access
Machine Learning in Maritime Safety for Autonomous Shipping: A Bibliometric Review and Future Trends
Jie Xue, Peijie Yang, Qiang Li, et al.
Journal of Marine Science and Engineering (2025) Vol. 13, Iss. 4, pp. 746-746
Open Access
Unsupervised fault diagnosis framework for underwater thruster system using estimated torques and multi-head convolutional autoencoder
Shuang Gao, Chen Feng, Xin Zhang, et al.
Mechanical Systems and Signal Processing (2023) Vol. 205, pp. 110814-110814
Closed Access | Times Cited: 7
The Use of eXplainable Artificial Intelligence and Machine Learning Operation Principles to Support the Continuous Development of Machine Learning-Based Solutions in Fault Detection and Identification
Tuan-anh Tran, Tamás Ruppert, János Abonyi
Computers (2024) Vol. 13, Iss. 10, pp. 252-252
Open Access | Times Cited: 2
Attention mechanism‐based multisensor data fusion neural network for fault diagnosis of autonomous underwater vehicles
Huaitao Shi, Zelong Song, Xiaotian Bai, et al.
Journal of Field Robotics (2023)
Closed Access | Times Cited: 5
Artificial Intelligence Models for Predicting Ground Vibrations in Deep Underground Mines to Ensure the Safety of Their Surroundings
Yunbo Tao, Qiusong Chen, Chongchun Xiao, et al.
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4771-4771
Open Access | Times Cited: 1
Time-Efficient Neural Architecture Search for Autonomous Underwater Vehicle Fault Diagnosis
Shicheng Pei, Huan Wang, Te Han
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-11
Closed Access | Times Cited: 3
Research on the Optimal Mode of Motion in Water Polo
椿琛 唐
Modeling and Simulation (2024) Vol. 13, Iss. 03, pp. 2943-2953
Closed Access
Hybrid fault diagnosis method for underwater thrusters based on the common features of multi-source signals
Shuang Gao, Ying Wang, Zhiyao Zhang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 222, pp. 111740-111740
Closed Access
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