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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:

Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction
Mohamed Ragab, Zhenghua Chen, Min Wu, et al.
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 8, pp. 5239-5249
Open Access | Times Cited: 121

Showing 1-25 of 121 citing articles:

Bi-LSTM-Based Two-Stream Network for Machine Remaining Useful Life Prediction
Ruibing Jin, Zhenghua Chen, Keyu Wu, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-10
Closed Access | Times Cited: 82
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 survey of transfer learning for machinery diagnostics and prognostics
Siya Yao, Qi Kang, MengChu Zhou, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 4, pp. 2871-2922
Closed Access | Times Cited: 74
A new supervised multi-head self-attention autoencoder for health indicator construction and similarity-based machinery RUL prediction
Yi Qin, Jiahong Yang, Jianghong Zhou, et al.
Advanced Engineering Informatics (2023) Vol. 56, pp. 101973-101973
Closed Access | Times Cited: 51
A multi-phase Wiener process-based degradation model with imperfect maintenance activities
Jie Ma, Li Cai, Guobo Liao, et al.
Reliability Engineering & System Safety (2023) Vol. 232, pp. 109075-109075
Closed Access | Times Cited: 45
A Systematic Literature Review on Transfer Learning for Predictive Maintenance in Industry 4.0
Mehdi Saman Azari, Francesco Flammini, Stefania Santini, et al.
IEEE Access (2023) Vol. 11, pp. 12887-12910
Open Access | Times Cited: 42
Data-Driven Remaining Useful Life Estimation for Milling Process: Sensors, Algorithms, Datasets, and Future Directions
Sameer Sayyad, Satish Kumar, Arunkumar Bongale, et al.
IEEE Access (2021) Vol. 9, pp. 110255-110286
Open Access | Times Cited: 79
Remaining useful life prediction of bearings under different working conditions using a deep feature disentanglement based transfer learning method
Tao Hu, Yiming Guo, Liudong Gu, et al.
Reliability Engineering & System Safety (2021) Vol. 219, pp. 108265-108265
Closed Access | Times Cited: 77
KDnet-RUL: A Knowledge Distillation Framework to Compress Deep Neural Networks for Machine Remaining Useful Life Prediction
Qing Xu, Zhenghua Chen, Keyu Wu, et al.
IEEE Transactions on Industrial Electronics (2021) Vol. 69, Iss. 2, pp. 2022-2032
Closed Access | Times Cited: 73
Remaining Useful Life Estimation Under Multiple Operating Conditions via Deep Subdomain Adaptation
Yifei Ding, Minping Jia, Yudong Cao
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-11
Closed Access | Times Cited: 70
Generalized multiscale feature extraction for remaining useful life prediction of bearings with generative adversarial networks
Sungho Suh, Paul Lukowicz, Yong Oh Lee
Knowledge-Based Systems (2021) Vol. 237, pp. 107866-107866
Open Access | Times Cited: 67
An adversarial transfer network with supervised metric for remaining useful life prediction of rolling bearing under multiple working conditions
Jichao Zhuang, Minping Jia, Xiaoli Zhao
Reliability Engineering & System Safety (2022) Vol. 225, pp. 108599-108599
Closed Access | Times Cited: 57
The two-stage RUL prediction across operation conditions using deep transfer learning and insufficient degradation data
Han Cheng, Xianguang Kong, Qibin Wang, et al.
Reliability Engineering & System Safety (2022) Vol. 225, pp. 108581-108581
Closed Access | Times Cited: 52
Self-Supervised Deep Domain-Adversarial Regression Adaptation for Online Remaining Useful Life Prediction of Rolling Bearing Under Unknown Working Condition
Wentao Mao, Jiaxian Chen, Jing Liu, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 2, pp. 1227-1237
Closed Access | Times Cited: 52
Dynamic Model-Assisted Bearing Remaining Useful Life Prediction Using the Cross-Domain Transformer Network
Yongchao Zhang, Ke Feng, Jinchen Ji, et al.
IEEE/ASME Transactions on Mechatronics (2022) Vol. 28, Iss. 2, pp. 1070-1080
Closed Access | Times Cited: 49
Domain generalization via adversarial out-domain augmentation for remaining useful life prediction of bearings under unseen conditions
Yifei Ding, Minping Jia, Yudong Cao, et al.
Knowledge-Based Systems (2022) Vol. 261, pp. 110199-110199
Closed Access | Times Cited: 46
Remaining useful life estimation of bearings under different working conditions via Wasserstein distance-based weighted domain adaptation
Tao Hu, Yiming Guo, Liudong Gu, et al.
Reliability Engineering & System Safety (2022) Vol. 224, pp. 108526-108526
Closed Access | Times Cited: 40
Remaining useful life prediction of bearings using multi-source adversarial online regression under online unknown conditions
Jichao Zhuang, Yudong Cao, Minping Jia, et al.
Expert Systems with Applications (2023) Vol. 227, pp. 120276-120276
Closed Access | Times Cited: 23
Deep transfer learning-based hierarchical adaptive remaining useful life prediction of bearings considering the correlation of multistage degradation
Han-Bing Zhang, De-Jun Cheng, Kaili Zhou, et al.
Knowledge-Based Systems (2023) Vol. 266, pp. 110391-110391
Closed Access | Times Cited: 22
Deep Learning for Time-Series Prediction in IIoT: Progress, Challenges, and Prospects
Lei Ren, Zidi Jia, Yuanjun Laili, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023), pp. 1-20
Open Access | Times Cited: 22
Contrastive BiLSTM-enabled Health Representation Learning for Remaining Useful Life Prediction
Qixiang Zhu, Zheng Zhou, Yasong Li, et al.
Reliability Engineering & System Safety (2024) Vol. 249, pp. 110210-110210
Closed Access | Times Cited: 11
Meta-learning with deep flow kernel network for few shot cross-domain remaining useful life prediction
Jing Yang, Xiaomin Wang
Reliability Engineering & System Safety (2024) Vol. 244, pp. 109928-109928
Closed Access | Times Cited: 10
Multidimensional Attention Domain Adaptive Method Incorporating Degradation Prior for Machine Remaining Useful Life Prediction
Shushuai Xie, Wei Cheng, Zelin Nie, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 5, pp. 7345-7356
Closed Access | Times Cited: 10
Artificial intelligence enhanced fault prediction with industrial incomplete information
Xiaoyan Shao, Baoping Cai, Zhexian Zou, et al.
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 112063-112063
Closed Access | Times Cited: 9
Pre-training enhanced unsupervised contrastive domain adaptation for industrial equipment remaining useful life prediction
Haodong Li, Peng Cao, X. Wang, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102517-102517
Closed Access | Times Cited: 7
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