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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 dual-LSTM framework combining change point detection and remaining useful life prediction
Zunya Shi, Abdallah Chehade
Reliability Engineering & System Safety (2020) Vol. 205, pp. 107257-107257
Closed Access | Times Cited: 248

Showing 1-25 of 248 citing articles:

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
Fusing physics-based and deep learning models for prognostics
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, et al.
Reliability Engineering & System Safety (2021) Vol. 217, pp. 107961-107961
Open Access | Times Cited: 246
A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings
Yudong Cao, Yifei Ding, Minping Jia, et al.
Reliability Engineering & System Safety (2021) Vol. 215, pp. 107813-107813
Closed Access | Times Cited: 233
Prediction of remaining useful life based on bidirectional gated recurrent unit with temporal self-attention mechanism
Jiusi Zhang, Yuchen Jiang, Shimeng Wu, et al.
Reliability Engineering & System Safety (2022) Vol. 221, pp. 108297-108297
Closed Access | Times Cited: 229
Transformer Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Daoquan Chen, Wei-Cong Hong, Xiuze Zhou
IEEE Access (2022) Vol. 10, pp. 19621-19628
Open Access | Times Cited: 182
Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnostics
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, et al.
Data (2021) Vol. 6, Iss. 1, pp. 5-5
Open Access | Times Cited: 177
Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture
Lu Liu, Xiao Song, Zhetao Zhou
Reliability Engineering & System Safety (2022) Vol. 221, pp. 108330-108330
Closed Access | Times Cited: 157
Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction
Sheng Xiang, Yi Qin, Jun Luo, et al.
Reliability Engineering & System Safety (2021) Vol. 216, pp. 107927-107927
Closed Access | Times Cited: 146
Hierarchical attention graph convolutional network to fuse multi-sensor signals for remaining useful life prediction
Tianfu Li, Zhibin Zhao, Chuang Sun, et al.
Reliability Engineering & System Safety (2021) Vol. 215, pp. 107878-107878
Closed Access | Times Cited: 146
Transfer learning for remaining useful life prediction of multi-conditions bearings based on bidirectional-GRU network
Yudong Cao, Minping Jia, Peng Ding, et al.
Measurement (2021) Vol. 178, pp. 109287-109287
Closed Access | Times Cited: 142
Long short-term memory network with Bayesian optimization for health prognostics of lithium-ion batteries based on partial incremental capacity analysis
Huixing Meng, Mengyao Geng, Te Han
Reliability Engineering & System Safety (2023) Vol. 236, pp. 109288-109288
Closed Access | Times Cited: 130
An adaptive remaining useful life prediction approach for single battery with unlabeled small sample data and parameter uncertainty
Jiusi Zhang, Yuchen Jiang, Xiang Li, et al.
Reliability Engineering & System Safety (2022) Vol. 222, pp. 108357-108357
Closed Access | Times Cited: 114
FGDAE: A new machinery anomaly detection method towards complex operating conditions
Shen Yan, Haidong Shao, Zhishan Min, et al.
Reliability Engineering & System Safety (2023) Vol. 236, pp. 109319-109319
Open Access | Times Cited: 113
Prediction of remaining useful life of multi-stage aero-engine based on clustering and LSTM fusion
Junqiang Liu, Lei Fan, Pan Chunlu, et al.
Reliability Engineering & System Safety (2021) Vol. 214, pp. 107807-107807
Closed Access | Times Cited: 105
Remaining useful life prediction of bearings by a new reinforced memory GRU network
Jianghong Zhou, Yi Qin, Dingliang Chen, et al.
Advanced Engineering Informatics (2022) Vol. 53, pp. 101682-101682
Closed Access | Times Cited: 84
Variational encoding approach for interpretable assessment of remaining useful life estimation
Nahuel Costa, Luciano Sánchez
Reliability Engineering & System Safety (2022) Vol. 222, pp. 108353-108353
Open Access | Times Cited: 79
A Comprehensive Review of Lithium-Ion Batteries Modeling, and State of Health and Remaining Useful Lifetime Prediction
Mohamed Elmahallawy, Tarek Elfouly, A.T. Alouani, et al.
IEEE Access (2022) Vol. 10, pp. 119040-119070
Open Access | Times Cited: 76
Multivariate stacked bidirectional long short term memory for lithium-ion battery health management
Reza Rouhi Ardeshiri, Ming Liu, Chengbin Ma
Reliability Engineering & System Safety (2022) Vol. 224, pp. 108481-108481
Closed Access | Times Cited: 69
Integration of deep learning and Bayesian networks for condition and operation risk monitoring of complex engineering systems
Ramin Moradi, Sergio Cofre-Martel, Enrique López Droguett, et al.
Reliability Engineering & System Safety (2022) Vol. 222, pp. 108433-108433
Closed Access | Times Cited: 68
Bearing remaining useful life prediction with convolutional long short-term memory fusion networks
Shaoke Wan, Xiaohu Li, Yanfei Zhang, et al.
Reliability Engineering & System Safety (2022) Vol. 224, pp. 108528-108528
Closed Access | Times Cited: 68
Remaining useful life prediction of aero-engine enabled by fusing knowledge and deep learning models
Yuanfu Li, Yao Chen, Zhenchao Hu, et al.
Reliability Engineering & System Safety (2022) Vol. 229, pp. 108869-108869
Closed Access | Times Cited: 68
A controllable deep transfer learning network with multiple domain adaptation for battery state-of-charge estimation
Isaiah Oyewole, Abdallah Chehade, Youngki Kim
Applied Energy (2022) Vol. 312, pp. 118726-118726
Closed Access | Times Cited: 67
A novel entropy-based sparsity measure for prognosis of bearing defects and development of a sparsogram to select sensitive filtering band of an axial piston pump
Yuqing Zhou, Anil Kumar, Chander Parkash, et al.
Measurement (2022) Vol. 203, pp. 111997-111997
Closed Access | Times Cited: 67
Deep Learning Techniques in Intelligent Fault Diagnosis and Prognosis for Industrial Systems: A Review
Shaohua Qiu, Xiaopeng Cui, Zuowei Ping, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1305-1305
Open Access | Times Cited: 65
A CNN and LSTM-based multi-task learning architecture for short and medium-term electricity load forecasting
Shiyun Zhang, Runhuan Chen, Jiacheng Cao, et al.
Electric Power Systems Research (2023) Vol. 222, pp. 109507-109507
Closed Access | Times Cited: 51
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