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:

Monitoring and detecting coal miners' fatigue status using MPA-LSSVM in the vision of smart mine
Ying Chen, Caiwu Lu, Shuicheng Tian, et al.
Process Safety and Environmental Protection (2023) Vol. 179, pp. 774-783
Closed Access | Times Cited: 9

Showing 9 citing articles:

The digital twins for mine site rescue environment: Application framework and key technologies
Hu Wen, Shengkai Liu, Xuezhao Zheng, et al.
Process Safety and Environmental Protection (2024) Vol. 186, pp. 176-188
Closed Access | Times Cited: 5

The Impact of Task Interruptions on the Unsafe Behavior of Coal Mine Tunneling Machine Operators: The Moderating Role of Fatigue
Guangtong Shao, Shuicheng Tian, Fangyuan Tian, et al.
Applied Sciences (2025) Vol. 15, Iss. 5, pp. 2764-2764
Open Access

Research on the fatigue level of underground mine truck drivers with integration of cardiovascular and brain features
Ying Chen, Shengwei Li, Song Jiang, et al.
Journal of Loss Prevention in the Process Industries (2024) Vol. 89, pp. 105315-105315
Closed Access | Times Cited: 2

Assessment of the benefits of cooling vests on working conditions of mine operators in hard climatic conditions: A case study
Anna Lubosz, Janusz Smoliło, Małgorzata Chmiela, et al.
Journal of industrial safety. (2024) Vol. 1, Iss. 1, pp. 100001-100001
Open Access | Times Cited: 1

A study of asymmetric guided wave propagation mechanism in elbow and prediction of elbow erosion degree based on SAFE and GA-LSSVM methods
Zhaokun Wang, Ning Li, Sizhu Zhou
Measurement (2024) Vol. 240, pp. 115542-115542
Closed Access | Times Cited: 1

Research on work-stress recognition for deep ground miners based on depth-separable convolutional neural network
Ying Chen, Yuehan Liu, Caiwu Lu, et al.
Journal of Loss Prevention in the Process Industries (2024) Vol. 91, pp. 105410-105410
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

Research on the Effects of Operational Fatigue and Bagging-SVM Recognition of Deep Coal Mine Workers
Ying Chen, Peishuo Chai, Qinghua Gu, et al.
Journal of Loss Prevention in the Process Industries (2024), pp. 105508-105508
Closed Access

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