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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:

LSTM networks based on attention ordered neurons for gear remaining life prediction
Sheng Xiang, Yi Qin, Caichao Zhu, et al.
ISA Transactions (2020) Vol. 106, pp. 343-354
Closed Access | Times Cited: 84

Showing 1-25 of 84 citing articles:

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
Dual-Aspect Self-Attention Based on Transformer for Remaining Useful Life Prediction
Zhizheng Zhang, Wen Song, Qiqiang Li
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-11
Open Access | Times Cited: 164
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
Short-term wind power forecasting based on Attention Mechanism and Deep Learning
Bangru Xiong, Lu Lou, Xinyu Meng, et al.
Electric Power Systems Research (2022) Vol. 206, pp. 107776-107776
Closed Access | Times Cited: 102
Spatial correlation and temporal attention-based LSTM for remaining useful life prediction of turbofan engine
Huixin Tian, Linzheng Yang, Bingtian Ju
Measurement (2023) Vol. 214, pp. 112816-112816
Closed Access | Times Cited: 61
A dual attention LSTM lightweight model based on exponential smoothing for remaining useful life prediction
Jiayu Shi, Jingshu Zhong, Yuxuan Zhang, et al.
Reliability Engineering & System Safety (2023) Vol. 243, pp. 109821-109821
Closed Access | Times Cited: 41
Health indicator construction by quadratic function-based deep convolutional auto-encoder and its application into bearing RUL prediction
Dingliang Chen, Yi Qin, Yi Wang, et al.
ISA Transactions (2020) Vol. 114, pp. 44-56
Closed Access | Times Cited: 131
Self-Attention ConvLSTM and Its Application in RUL Prediction of Rolling Bearings
Biao Li, Baoping Tang, Lei Deng, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-11
Closed Access | Times Cited: 86
Digital Twin-Driven Remaining Useful Life Prediction for Gear Performance Degradation: A Review
Bin He, Long Liu, Dong Zhang
Journal of Computing and Information Science in Engineering (2021) Vol. 21, Iss. 3
Closed Access | Times Cited: 66
Efficient temporal flow Transformer accompanied with multi-head probsparse self-attention mechanism for remaining useful life prognostics
Yuanhong Chang, Fudong Li, Jinglong Chen, et al.
Reliability Engineering & System Safety (2022) Vol. 226, pp. 108701-108701
Closed Access | Times Cited: 60
Trend attention fully convolutional network for remaining useful life estimation
Linchuan Fan, Yi Chai, Xiaolong Chen
Reliability Engineering & System Safety (2022) Vol. 225, pp. 108590-108590
Closed Access | Times Cited: 53
RUL prediction of machinery using convolutional-vector fusion network through multi-feature dynamic weighting
Xiaofei Liu, Yaguo Lei, Naipeng Li, et al.
Mechanical Systems and Signal Processing (2022) Vol. 185, pp. 109788-109788
Closed Access | Times Cited: 52
A concise self-adapting deep learning network for machine remaining useful life prediction
Sheng Xiang, Yi Qin, Jun Luo, et al.
Mechanical Systems and Signal Processing (2023) Vol. 191, pp. 110187-110187
Closed Access | Times Cited: 27
Cocktail LSTM and Its Application Into Machine Remaining Useful Life Prediction
Sheng Xiang, Jianghong Zhou, Jun Luo, et al.
IEEE/ASME Transactions on Mechatronics (2023) Vol. 28, Iss. 5, pp. 2425-2436
Closed Access | Times Cited: 24
LSTM-Autoencoder Based Anomaly Detection Using Vibration Data of Wind Turbines
Younjeong Lee, Chanho Park, Namji Kim, et al.
Sensors (2024) Vol. 24, Iss. 9, pp. 2833-2833
Open Access | Times Cited: 9
Ensemble empirical mode decomposition energy moment entropy and enhanced long short-term memory for early fault prediction of bearing
Zehai Gao, Yang Liu, Quanjiu Wang, et al.
Measurement (2021) Vol. 188, pp. 110417-110417
Closed Access | Times Cited: 44
Remaining useful life prediction for rolling bearings using multi-layer grid search and LSTM
Zihan Chang, Wei Yuan, Kou Huang
Computers & Electrical Engineering (2022) Vol. 101, pp. 108083-108083
Closed Access | Times Cited: 36
An Echo State Network With Improved Topology for Time Series Prediction
Xin Li, Fengrong Bi, Xiao Yang, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 6, pp. 5869-5878
Closed Access | Times Cited: 28
A Novel Convolution Network Based on Temporal Attention Fusion Mechanism for Remaining Useful Life Prediction of Rolling Bearings
Zong Meng, Bo Xu, Lixiao Cao, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 4, pp. 3990-3999
Closed Access | Times Cited: 18
Estimating remaining useful life of rotating machinery using relevance vector machine and deep learning network
Lele Li, Jiawang Xu, Juguang Li
Engineering Failure Analysis (2023) Vol. 146, pp. 107125-107125
Closed Access | Times Cited: 18
A novel gear RUL prediction method by diffusion model generation health index and attention guided multi-hierarchy LSTM
Xinping Chen
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 6
A Remaining Useful Life Prediction Method of Rolling Bearings Based on Deep Reinforcement Learning
Zheng Guokang, Yasong Li, Zheng Zhou, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 13, pp. 22938-22949
Closed Access | Times Cited: 6
Non-Temporal Neural Networks for Predicting Degradation Trends of Key Wind-Turbine Gearbox Components
Xiaoxia Yu, Zhigang Zhang, Baoping Tang, et al.
Renewable Energy (2025), pp. 122438-122438
Closed Access
Remaining Useful Life Prediction of Rolling Bearings Based on Multiscale Convolutional Neural Network with Integrated Dilated Convolution Blocks
Ran Wang, Ruyu Shi, Xiong Hu, et al.
Shock and Vibration (2021) Vol. 2021, pp. 1-11
Open Access | Times Cited: 32
Ultrasonic Lamb wave mixing based fatigue crack detection using a deep learning model and higher-order spectral analysis
Santhakumar Sampath, Jinho Jang, Hoon Sohn
International Journal of Fatigue (2022) Vol. 163, pp. 107028-107028
Closed Access | Times Cited: 24
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