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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:

Prognostics of Remaining Useful Life for Lithium-Ion Batteries Based on Hybrid Approach of Linear Pattern Extraction and Nonlinear Relationship Mining
Yingzhou Wang, Chenyang Hei, Hui Liu, et al.
IEEE Transactions on Power Electronics (2022) Vol. 38, Iss. 1, pp. 1054-1063
Closed Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

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: 74
Remaining Useful Life Prediction for Lithium-Ion Batteries With a Hybrid Model Based on TCN-GRU-DNN and Dual Attention Mechanism
Lei Li, Y. G. Li, Runze Mao, et al.
IEEE Transactions on Transportation Electrification (2023) Vol. 9, Iss. 3, pp. 4726-4740
Closed Access | Times Cited: 63
A multi-scale learning approach for remaining useful life prediction of lithium-ion batteries based on variational mode decomposition and Monte Carlo sampling
Meng Wei, Min Ye, Chuanwei Zhang, et al.
Energy (2023) Vol. 283, pp. 129086-129086
Closed Access | Times Cited: 24
Lithium-ion battery health state and remaining useful life prediction based on hybrid model MFE-GRU-TCA
Xiaohua Wang, Ke Dai, Min Hu, et al.
Journal of Energy Storage (2024) Vol. 95, pp. 112442-112442
Closed Access | Times Cited: 10
A structural pruning method for lithium-ion batteries remaining useful life prediction model with multi-head attention mechanism
Ge Yang, Jiaxin Ma, Guodong Sun
Journal of Energy Storage (2024) Vol. 86, pp. 111396-111396
Closed Access | Times Cited: 7
Collaborative Prediction Model for Rul and Soh of Li-Ion Batteries Using Multi-Source Feature Selection and Mixed Quadratic Modal Decomposition-Dbn
Yan Zhang, Yu Wu, K. Z. Shang, et al.
(2025)
Closed Access
Prior task aware-augmented meta learning for early state-of-health estimation of lithium-ion batteries
Jing Yang, Minglan Zhang, Xiaomin Wang
Energy (2025), pp. 135648-135648
Closed Access
A novel RUL prediction framework based on the adaptability feature perception fusion model method
Jiabo Li, Zhixuan Wang, Di Tian, et al.
Journal of Energy Storage (2025) Vol. 119, pp. 116322-116322
Closed Access
Reimagining Literary Analysis: Utilizing Artificial Intelligence to Classify Modernist French Poetry
Yang Liu, Gang Wang, Hongjun Wang
Information (2024) Vol. 15, Iss. 2, pp. 70-70
Open Access | Times Cited: 4
Comparing Hybrid Approaches of Deep Learning for Remaining Useful Life Prognostic of Lithium-Ion Batteries
Anas Tiane, Chafik Okar, Mohamad Alzayed, et al.
IEEE Access (2024) Vol. 12, pp. 70334-70344
Open Access | Times Cited: 4
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
M. S. Reza, M. A. Hannan, Muhamad Mansor, et al.
Journal of Energy Storage (2024) Vol. 98, pp. 113056-113056
Closed Access | Times Cited: 4
A novel feature adaptive meta-model for efficient remaining useful life prediction of lithium-ion batteries
Amit Kumar, J. Jay Liu
Journal of Energy Storage (2025) Vol. 114, pp. 115715-115715
Closed 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
Confidence-aware Quantile Transformer for reliable degradation prediction of battery energy storage systems
Rui Wu, Jinpeng Tian, Jiachi Yao, et al.
Reliability Engineering & System Safety (2025), pp. 111019-111019
Closed Access
Deep Koopman operator-based remaining useful life prediction of Lithium-ion batteries under multi-condition scenarios
Ge Yang, Xingxing Jiang, Benlian Xu
Journal of Energy Storage (2025) Vol. 119, pp. 116369-116369
Closed Access
Capacity Estimation for Lithium-ion Batteries Based on Impedance Spectral Dynamics and Deep Gaussian Process
Shude Zhang, Weiru Yuan, Yingzhou Wang, et al.
IEEE Transactions on Power Electronics (2024) Vol. 39, Iss. 8, pp. 10287-10298
Closed Access | Times Cited: 3
A heterogeneous learner fusion method with supplementary feature for lithium-ion batteries state of health estimation
Hailin Feng, Lu Zhang
Journal of Energy Storage (2024) Vol. 92, pp. 111896-111896
Closed Access | Times Cited: 3
Applying Neural Network to Health Estimation and Lifetime Prediction of Lithium-ion Batteries
Penghua Li, Xiankui Wu, Radu Grosu, et al.
IEEE Transactions on Transportation Electrification (2024) Vol. 11, Iss. 1, pp. 4224-4248
Closed Access | Times Cited: 3
A hybrid remaining useful life prediction method for lithium-ion batteries based on transfer learning with CDRSN-BiGRU-AM
Lei Li, Y. G. Li, J. L. Zhang
Measurement Science and Technology (2024) Vol. 35, Iss. 5, pp. 056124-056124
Closed Access | Times Cited: 2
A novel remaining useful life prediction method based on gated recurrent unit network optimized by tunicate swarm algorithm for lithium-ion batteries
Q. Zhai, Jing Sun, Yunlong Shang, et al.
Transactions of the Institute of Measurement and Control (2024)
Closed Access | Times Cited: 2
A MDA-LSTM network for remaining useful life estimation of lithium batteries
Xiaohua Wang, Nanbing Ni, Min Hu, et al.
Signal Image and Video Processing (2024) Vol. 18, Iss. S1, pp. 129-140
Closed Access | Times Cited: 1
Adaptive Sliding Window–Dynamic Time Warping-Based Fluctuation Series Prediction for the Capacity of Lithium-Ion Batteries
Sihan Sun, Minming Gu, Tuoqi Liu
Electronics (2024) Vol. 13, Iss. 13, pp. 2501-2501
Open Access | Times Cited: 1
Gravitational Search Algorithm based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty
M. S. Reza, M. A. Hannan, Muhamad Mansor, et al.
IEEE Transactions on Industry Applications (2024) Vol. 60, Iss. 6, pp. 9171-9183
Closed Access | Times Cited: 1
Remaining useful life prediction of lithium-ion batteries based on FEEMD-LSTM-TAM-OKELM
Jianwei Yu, Yaoyang Cai, Yingxin Huang, et al.
AIP Advances (2024) Vol. 14, Iss. 11
Open Access | Times Cited: 1
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