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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 Novel Competitive Temporal Convolutional Network for Remaining Useful Life Prediction of Rolling Bearings
Wei Wang, Gongbo Zhou, Guoqing Ma, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 12

Showing 12 citing articles:

A bearing remaining life prediction method under variable operating conditions based on cross-transformer fusioning segmented data cleaning
Dongxiao Hou, Jiahui Chen, Rongcai Cheng, et al.
Reliability Engineering & System Safety (2024) Vol. 245, pp. 110021-110021
Closed Access | Times Cited: 6
Cross-domain remaining useful life prediction for rolling bearings based on wavelet decomposition and dynamic calibrated domain adaptive networks
Yazhou Zhang, Xiaoqiang Zhao, Zhenrui Peng, et al.
Measurement (2025), pp. 117278-117278
Closed Access
A dual-stream temporal convolutional network for remaining useful life prediction of rolling bearings
Yazhou Zhang, Xiaoqiang Zhao, Rongrong Xu, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 1, pp. 016206-016206
Closed Access | Times Cited: 3
A novel approach based on spatio-temporal attention and multi-scale modeling for mechanical failure prediction
Weimin Zhai, Weiming Fu, Jiahu Qin, et al.
Control Engineering Practice (2024) Vol. 147, pp. 105938-105938
Closed Access | Times Cited: 2
Degradation-Trend-Aware Deep Neural Network With Attention Mechanism for Bearing Remaining Useful Life Prediction
Yongkang Liu, Donghui Pan, Haifeng Zhang, et al.
IEEE Transactions on Artificial Intelligence (2023) Vol. 5, Iss. 6, pp. 2997-3011
Closed Access | Times Cited: 6
Similarity indicator and CG-CGAN prediction model for remaining useful life of rolling bearings
Yang Liu, Binbin Dan, Cancan Yi, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086107-086107
Open Access | Times Cited: 1
A Novel RUL-Centric Data Augmentation Method for Predicting the Remaining Useful Life of Bearings
Miao He, Zhonghua Li, Fangchao Hu
Machines (2024) Vol. 12, Iss. 11, pp. 766-766
Open Access | Times Cited: 1
Explainable Anomaly Detection: Counterfactual driven What-If Analysis
Logan Cummins, Alexander Sommers, Sudip Mittal, et al.
(2024), pp. 144-151
Closed Access | Times Cited: 1
A Novel Method for Multistage Degradation Predicting the Remaining Useful Life of Wind Turbine Generator Bearings Based on Domain Adaptation
Miao Tian, Xiaoming Su, Changzheng Chen, et al.
Applied Sciences (2023) Vol. 13, Iss. 22, pp. 12332-12332
Open Access | Times Cited: 3
Intelligent Status Diagnosis System for Water Circulation Device
Jeng-Dao Lee, Yu-Cheng Ye, Chi‐Ting Ho, et al.
(2024), pp. 1-3
Closed Access
Remaining useful life prediction method of bearings based on the interactive learning strategy
Hao Wang, Jing An, Jun Yang, et al.
Computers & Electrical Engineering (2024) Vol. 121, pp. 109853-109853
Closed Access
CRULP: Reliable RUL Estimation Inspired by Conformal Prediction
Shiyuan Piao, Ruyi Huang, Fugee Tsung
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 74, pp. 1-11
Closed Access
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