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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:

Bayesian Deep-Learning-Based Health Prognostics Toward Prognostics Uncertainty
Weiwen Peng, Zhi‐Sheng Ye, Nan Chen
IEEE Transactions on Industrial Electronics (2019) Vol. 67, Iss. 3, pp. 2283-2293
Closed Access | Times Cited: 209

Showing 1-25 of 209 citing articles:

A comprehensive review on convolutional neural network in machine fault diagnosis
Jinyang Jiao, Ming Zhao, Jing Lin, et al.
Neurocomputing (2020) Vol. 417, pp. 36-63
Open Access | Times Cited: 403
Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice
Enrico Zio
Reliability Engineering & System Safety (2021) Vol. 218, pp. 108119-108119
Open Access | Times Cited: 372
A new data-driven transferable remaining useful life prediction approach for bearing under different working conditions
Jun Zhu, Nan Chen, Changqing Shen
Mechanical Systems and Signal Processing (2020) Vol. 139, pp. 106602-106602
Closed Access | Times Cited: 251
Deep learning for prognostics and health management: State of the art, challenges, and opportunities
Behnoush Rezaeianjouybari, Yi Shang
Measurement (2020) Vol. 163, pp. 107929-107929
Closed Access | Times Cited: 231
Health status assessment and remaining useful life prediction of aero-engine based on BiGRU and MMoE
Yong Zhang, Yuqi Xin, Zhi‐Wei Liu, et al.
Reliability Engineering & System Safety (2021) Vol. 220, pp. 108263-108263
Closed Access | Times Cited: 164
Recent advances and trends of predictive maintenance from data-driven machine prognostics perspective
Yuxin Wen, Md Fashiar Rahman, Honglun Xu, et al.
Measurement (2021) Vol. 187, pp. 110276-110276
Open Access | Times Cited: 146
A novel deep convolutional neural network-bootstrap integrated method for RUL prediction of rolling bearing
Cheng‐Geng Huang, Hong‐Zhong Huang, Yan‐Feng Li, et al.
Journal of Manufacturing Systems (2021) Vol. 61, pp. 757-772
Closed Access | Times Cited: 143
A prognostic driven predictive maintenance framework based on Bayesian deep learning
Liangliang Zhuang, Ancha Xu, Xiaolin Wang
Reliability Engineering & System Safety (2023) Vol. 234, pp. 109181-109181
Closed Access | Times Cited: 91
A Calibration-Based Hybrid Transfer Learning Framework for RUL Prediction of Rolling Bearing Across Different Machines
Yafei Deng, Shichang Du, Dong Wang, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-15
Closed Access | Times Cited: 86
Bayesian deep-learning for RUL prediction: An active learning perspective
Rong Zhu, Yuan Chen, Weiwen Peng, et al.
Reliability Engineering & System Safety (2022) Vol. 228, pp. 108758-108758
Closed Access | Times Cited: 84
Bayesian transfer learning with active querying for intelligent cross-machine fault prognosis under limited data
Rong Zhu, Weiwen Peng, Dong Wang, et al.
Mechanical Systems and Signal Processing (2022) Vol. 183, pp. 109628-109628
Closed Access | Times Cited: 81
A gated graph convolutional network with multi-sensor signals for remaining useful life prediction
Lei Wang, Hongrui Cao, Hao Xu, et al.
Knowledge-Based Systems (2022) Vol. 252, pp. 109340-109340
Closed Access | Times Cited: 76
Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
Venkat Pavan Nemani, Luca Biggio, Xun Huan, et al.
Mechanical Systems and Signal Processing (2023) Vol. 205, pp. 110796-110796
Open Access | Times Cited: 75
Optimizing prior distribution parameters for probabilistic prediction of remaining useful life using deep learning
You Keshun, Guangqi Qiu, Yingkui Gu
Reliability Engineering & System Safety (2023) Vol. 242, pp. 109793-109793
Closed Access | Times Cited: 45
Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review
Zhibin Zhao, Jingyao Wu, Tianfu Li, et al.
Chinese Journal of Mechanical Engineering (2021) Vol. 34, Iss. 1
Open Access | Times Cited: 98
A Bayesian Deep Learning RUL Framework Integrating Epistemic and Aleatoric Uncertainties
Gaoyang Li, Li Yang, Chi-Guhn Lee, et al.
IEEE Transactions on Industrial Electronics (2020) Vol. 68, Iss. 9, pp. 8829-8841
Closed Access | Times Cited: 96
Remaining Useful Life Prediction for Bearings Based on a Gated Recurrent Unit
Zijun Que, Xiaohang Jin, Zhengguo Xu
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-11
Closed Access | Times Cited: 96
A Bayesian deep learning framework for interval estimation of remaining useful life in complex systems by incorporating general degradation characteristics
Minhee Kim, Kaibo Liu
IISE Transactions (2020) Vol. 53, Iss. 3, pp. 326-340
Open Access | Times Cited: 93
Artificial intelligence in prognostics and health management of engineering systems
Sunday Ochella, Mahmood Shafiee, Fateme Dinmohammadi
Engineering Applications of Artificial Intelligence (2021) Vol. 108, pp. 104552-104552
Open Access | Times Cited: 91
Probabilistic Solar Irradiation Forecasting Based on Variational Bayesian Inference With Secure Federated Learning
Xiaoning Zhang, Fang Fang, Jiaqi Wang
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 11, pp. 7849-7859
Closed Access | Times Cited: 75
Prediction Interval Estimation of Aeroengine Remaining Useful Life Based on Bidirectional Long Short-Term Memory Network
Chuang Chen, Ningyun Lu, Bin Jiang, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-13
Closed Access | Times Cited: 73
State of health estimation for fast-charging lithium-ion battery based on incremental capacity analysis
Ruomei Zhou, Rong Zhu, Cheng‐Geng Huang, et al.
Journal of Energy Storage (2022) Vol. 51, pp. 104560-104560
Closed Access | Times Cited: 65
Meta deep learning based rotating machinery health prognostics toward few-shot prognostics
Peng Ding, Minping Jia, Xiaoli Zhao
Applied Soft Computing (2021) Vol. 104, pp. 107211-107211
Closed Access | Times Cited: 63
Autoencoder Quasi-Recurrent Neural Networks for Remaining Useful Life Prediction of Engineering Systems
Yiwei Cheng, Kui Hu, Jun Wu, et al.
IEEE/ASME Transactions on Mechatronics (2021) Vol. 27, Iss. 2, pp. 1081-1092
Closed Access | Times Cited: 63
A Bayesian Deep Learning Framework for RUL Prediction Incorporating Uncertainty Quantification and Calibration
Yan‐Hui Lin, Gang-Hui Li
IEEE Transactions on Industrial Informatics (2022) Vol. 18, Iss. 10, pp. 7274-7284
Closed Access | Times Cited: 59
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