Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

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

Showing 1-25 of 164 citing articles:

An integrated multi-head dual sparse self-attention network for remaining useful life prediction
Jiusi Zhang, Xiang Li, Jilun Tian, et al.
Reliability Engineering & System Safety (2023) Vol. 233, pp. 109096-109096
Closed Access | Times Cited: 119
A Parallel Hybrid Neural Network With Integration of Spatial and Temporal Features for Remaining Useful Life Prediction in Prognostics
Jiusi Zhang, Jilun Tian, Minglei Li, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 78
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
Battery prognostics and health management from a machine learning perspective
Jingyuan Zhao, Xuning Feng, Quanquan Pang, et al.
Journal of Power Sources (2023) Vol. 581, pp. 233474-233474
Closed Access | Times Cited: 60
A new convolutional dual-channel Transformer network with time window concatenation for remaining useful life prediction of rolling bearings
Li Jiang, Tianao Zhang, Lei Wei, et al.
Advanced Engineering Informatics (2023) Vol. 56, pp. 101966-101966
Closed Access | Times Cited: 54
Trend-augmented and temporal-featured Transformer network with multi-sensor signals for remaining useful life prediction
Yuru Zhang, Chun Su, Jiajun Wu, et al.
Reliability Engineering & System Safety (2023) Vol. 241, pp. 109662-109662
Closed Access | Times Cited: 45
Battery fault diagnosis and failure prognosis for electric vehicles using spatio-temporal transformer networks
Jingyuan Zhao, Xuning Feng, Junbin Wang, et al.
Applied Energy (2023) Vol. 352, pp. 121949-121949
Closed Access | Times Cited: 42
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
Artificial intelligence enabled self-powered wireless sensing for smart industry
Mingxuan Li, Zhengzhong Wan, Tianrui Zou, et al.
Chemical Engineering Journal (2024) Vol. 492, pp. 152417-152417
Closed Access | Times Cited: 25
AttMoE: Attention with Mixture of Experts for remaining useful life prediction of lithium-ion batteries
Daoquan Chen, Xiuze Zhou
Journal of Energy Storage (2024) Vol. 84, pp. 110780-110780
Closed Access | Times Cited: 17
A comparison study of centralized and decentralized federated learning approaches utilizing the transformer architecture for estimating remaining useful life
Sayaka Kamei, Sharareh Taghipour
Reliability Engineering & System Safety (2023) Vol. 233, pp. 109130-109130
Closed Access | Times Cited: 30
Global attention mechanism based deep learning for remaining useful life prediction of aero-engine
Zhiqiang Xu, Yujie Zhang, Jianguo Miao, et al.
Measurement (2023) Vol. 217, pp. 113098-113098
Closed Access | Times Cited: 30
Bayesian gated-transformer model for risk-aware prediction of aero-engine remaining useful life
Feifan Xiang, Yiming Zhang, Shuyou Zhang, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 121859-121859
Closed Access | Times Cited: 29
A Remaining Useful Life Prediction Method for Lithium-ion Battery Based on Temporal Transformer Network
Wenbin Song, Di Wu, Weiming Shen, et al.
Procedia Computer Science (2023) Vol. 217, pp. 1830-1838
Open Access | Times Cited: 28
Trans-Lighter: A light-weight federated learning-based architecture for Remaining Useful Lifetime prediction
Nguyen Huu Du, Nguyen Hoang Long, Kieu Ngan Ha, et al.
Computers in Industry (2023) Vol. 148, pp. 103888-103888
Closed Access | Times Cited: 28
Dual Self-Attention Swin Transformer for Hyperspectral Image Super-Resolution
Yaqian Long, Xun Wang, Meng Xu, et al.
IEEE Transactions on Geoscience and Remote Sensing (2023) Vol. 61, pp. 1-12
Closed Access | Times Cited: 25
DLformer: A Dynamic Length Transformer-Based Network for Efficient Feature Representation in Remaining Useful Life Prediction
Lei Ren, Haiteng Wang, Gao Huang
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 5, pp. 5942-5952
Closed Access | Times Cited: 24
A regularized constrained two-stream convolution augmented Transformer for aircraft engine remaining useful life prediction
Jiangyan Zhu, Jun Ma, Jiande Wu
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108161-108161
Closed Access | Times Cited: 12
An adaptive model with dual-dimensional attention for remaining useful life prediction of aero-engine
Fanfan Gan, Haidong Shao, Baizhan Xia
Knowledge-Based Systems (2024) Vol. 293, pp. 111738-111738
Closed Access | Times Cited: 12
Enhancing non-stationary feature learning for remaining useful life prediction of aero-engine under multiple operating conditions
Hao Liu, Youchao Sun, Wenhao Ding, et al.
Measurement (2024) Vol. 227, pp. 114242-114242
Closed Access | Times Cited: 8
A multiple conditions dual inputs attention network remaining useful life prediction method
Chengying Zhao, Huaitao Shi, Xianzhen Huang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108160-108160
Closed Access | Times Cited: 8
Local Enhancing Transformer With Temporal Convolutional Attention Mechanism for Bearings Remaining Useful Life Prediction
Huachao Peng, Bin Jiang, Zehui Mao, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-12
Closed Access | Times Cited: 18
DVGTformer: A dual-view graph Transformer to fuse multi-sensor signals for remaining useful life prediction
Lei Wang, Hongrui Cao, Zhi‐Sheng Ye, et al.
Mechanical Systems and Signal Processing (2023) Vol. 207, pp. 110935-110935
Closed Access | Times Cited: 18
Scalability, Explainability and Performance of Data-Driven Algorithms in Predicting the Remaining Useful Life: A Comprehensive Review
Somayeh Bakhtiari Ramezani, Logan Cummins, Brad Killen, et al.
IEEE Access (2023) Vol. 11, pp. 41741-41769
Open Access | Times Cited: 16
Using transformer and a reweighting technique to develop a remaining useful life estimation method for turbofan engines
Gyeongho Kim, Jae Gyeong Choi, Sunghoon Lim
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108475-108475
Closed Access | Times Cited: 7
Page 1 - Next Page

Scroll to top