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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:

Adaptive self-attention LSTM for RUL prediction of lithium-ion batteries
Zhuqing Wang, Ning Liu, Chilian Chen, et al.
Information Sciences (2023) Vol. 635, pp. 398-413
Closed Access | Times Cited: 73

Showing 1-25 of 73 citing articles:

Review on influence factors and prevention control technologies of lithium-ion battery energy storage safety
Youfu Lv, Xuewen Geng, Weiming Luo, et al.
Journal of Energy Storage (2023) Vol. 72, pp. 108389-108389
Closed Access | Times Cited: 51
A data-driven prediction model for the remaining useful life prediction of lithium-ion batteries
Juqiang Feng, Feng Cai, H. J. Li, et al.
Process Safety and Environmental Protection (2023) Vol. 180, pp. 601-615
Closed Access | Times Cited: 23
A transferable long-term lithium-ion battery aging trajectory prediction model considering internal resistance and capacity regeneration phenomenon
Yaodi Huang, Pengcheng Zhang, Jiahuan Lu, et al.
Applied Energy (2024) Vol. 360, pp. 122825-122825
Closed Access | Times Cited: 13
Deep machine learning approaches for battery health monitoring
Sanjeev Kumar Singh, P. R. Budarapu
Energy (2024) Vol. 300, pp. 131540-131540
Closed Access | Times Cited: 8
A deep learning framework for the joint prediction of the SOH and RUL of lithium-ion batteries based on bimodal images
Nian Cai, Xiaoping Que, Xu Zhang, et al.
Energy (2024) Vol. 302, pp. 131700-131700
Closed Access | Times Cited: 8
Recent Progress of Deep Learning Methods for Health Monitoring of Lithium-Ion Batteries
Seyed Saeed Madani, Carlos Ziebert, Parisa Vahdatkhah, et al.
Batteries (2024) Vol. 10, Iss. 6, pp. 204-204
Open Access | Times Cited: 8
Towards trustworthy remaining useful life prediction through multi-source information fusion and a novel LSTM-DAU model
Rui Bai, Khandaker Noman, Yu Yang, et al.
Reliability Engineering & System Safety (2024) Vol. 245, pp. 110047-110047
Closed Access | Times Cited: 7
Real‐time monitoring and ageing detection algorithm design with application on SiC‐based automotive power drive system
Pierpaolo Dini, Giovanni Basso, Sergio Saponara, et al.
IET Power Electronics (2024) Vol. 17, Iss. 6, pp. 690-710
Open Access | Times Cited: 7
A novel workflow including denoising and hybrid deep learning model for shield tunneling construction parameter prediction
Yuxian Zhang, Xuhua Ren, Jixun Zhang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108103-108103
Closed Access | Times Cited: 5
Multiscale modeling for enhanced battery health analysis: Pathways to longevity
Kaiyi Yang, Lisheng Zhang, Wentao Wang, et al.
Carbon Neutralization (2024) Vol. 3, Iss. 3, pp. 348-385
Open Access | Times Cited: 5
Machine learning for full lifecycle management of lithium-ion batteries
Qiangxiang Zhai, Hongmin Jiang, Nengbing Long, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 202, pp. 114647-114647
Closed Access | Times Cited: 5
Data-driven RUL prediction for lithium-ion batteries based on multilayer optimized fusion deep network
Bin Xu, Xuewu Ge, S JI, et al.
Ionics (2025)
Closed Access
Application of switching-input LSTM network for vessel trajectory prediction
Weihong Wang, Yi Zuo, Licheng Zhao, et al.
Applied Intelligence (2025) Vol. 55, Iss. 4
Closed Access
Improving predictive maintenance: Evaluating the impact of preprocessing and model complexity on the effectiveness of eXplainable Artificial Intelligence methods
M. Ndao, Genane Youness, Ndèye Niang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 144, pp. 110144-110144
Open Access
State of the Art in Electric Batteries’ State-of-Health (SoH) Estimation with Machine Learning: A Review
Giovane Ronei Sylvestrin, Joylan Nunes Maciel, Márcio Luís Munhoz Amorim, et al.
Energies (2025) Vol. 18, Iss. 3, pp. 746-746
Open Access
A novel remaining useful life prediction method based on CNN- Attention combined with SMA-GPR
Aina Tian, Haijun Yu, Zhengbang Hu, et al.
Energy (2025), pp. 135233-135233
Closed Access
Ultra-early prediction of lithium-ion battery cycle life based on assembled capacity curve extracted from a single cycle
Wenjin Yang, Hengzhao Yang
Journal of Power Sources (2025) Vol. 640, pp. 236620-236620
Closed Access
Prediction of Lithium Battery Voltage and State of Charge Using Multi-Head Attention BiLSTM Neural Network
Haiwen Xi, Taolin Lv, Jincheng Qin, et al.
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 3011-3011
Open Access
A novel dual attention mechanism combined with knowledge for remaining useful life prediction based on gated recurrent units
Yuanfu Li, Yifan Chen, Haonan Shao, et al.
Reliability Engineering & System Safety (2023) Vol. 239, pp. 109514-109514
Closed Access | Times Cited: 14
A critical review on prognostics for stochastic degrading systems under big data
Huiqin Li, Xiaosheng Si, Zhengxin Zhang, et al.
Fundamental Research (2024)
Open Access | Times Cited: 4
A novel parallel feature extraction-based multibatch process quality prediction method with application to a hot rolling mill process
Kai Zhang, Xiaowen Zhang, Kaixiang Peng
Journal of Process Control (2024) Vol. 135, pp. 103166-103166
Closed Access | Times Cited: 4
A Ship Energy Consumption Prediction Method Based on TGMA Model and Feature Selection
Yuhang Liu, Kai Wang, Yong Lu, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 7, pp. 1098-1098
Open Access | Times Cited: 4
A data and physical model joint driven method for lithium-ion battery remaining useful life prediction under complex dynamic conditions
Yi Ren, Ting Tang, Quan Xia, et al.
Journal of Energy Storage (2023) Vol. 79, pp. 110065-110065
Closed Access | Times Cited: 10
Battery health prognostics based on improved incremental capacity using a hybrid grey modeling and Gaussian process regression
Kailing Li, Naiming Xie
Energy (2024) Vol. 303, pp. 131888-131888
Closed Access | Times Cited: 3
Intelligent fault diagnosis for unbalanced battery data using adversarial domain expansion and enhanced stochastic configuration networks
Sizhe Liu, XU De-zhi, Yujian Ye, et al.
Information Sciences (2024) Vol. 687, pp. 121399-121399
Closed Access | Times Cited: 3
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