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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:

Bi-directional long short-term memory recurrent neural network with attention for stack voltage degradation from proton exchange membrane fuel cells
Fu‐Kwun Wang, Tadele Mamo, Xiao‐Bin Cheng
Journal of Power Sources (2020) Vol. 461, pp. 228170-228170
Closed Access | Times Cited: 93

Showing 1-25 of 93 citing articles:

A review on lifetime prediction of proton exchange membrane fuel cells system
Zhiguang Hua, Zhixue Zheng, Elodie Pahon, et al.
Journal of Power Sources (2022) Vol. 529, pp. 231256-231256
Open Access | Times Cited: 167
Online remaining useful life prediction of lithium-ion batteries using bidirectional long short-term memory with attention mechanism
Fu‐Kwun Wang, Zemenu Endalamaw Amogne, Jia‐Hong Chou, et al.
Energy (2022) Vol. 254, pp. 124344-124344
Closed Access | Times Cited: 100
A data-driven method for multi-step-ahead prediction and long-term prognostics of proton exchange membrane fuel cell
Khaled Benaggoune, Meiling Yue, Samir Jemeï, et al.
Applied Energy (2022) Vol. 313, pp. 118835-118835
Closed Access | Times Cited: 75
Machine learning based fault detection and state of health estimation of proton exchange membrane fuel cells
Vijay Mohan Nagulapati, S. Shiva Kumar, Vimalesh Annadurai, et al.
Energy and AI (2023) Vol. 12, pp. 100237-100237
Open Access | Times Cited: 39
Short-term performance degradation prediction of a commercial vehicle fuel cell system based on CNN and LSTM hybrid neural network
Bei Sun, Xudong Liu, Jiayuan Wang, et al.
International Journal of Hydrogen Energy (2022) Vol. 48, Iss. 23, pp. 8613-8628
Closed Access | Times Cited: 59
A novel long short-term memory networks-based data-driven prognostic strategy for proton exchange membrane fuel cells
Chu Wang, Zhongliang Li, Rachid Outbib, et al.
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 18, pp. 10395-10408
Open Access | Times Cited: 56
Remaining useful life prediction for proton exchange membrane fuel cells using combined convolutional neural network and recurrent neural network
Tabbi Wilberforce, Abed Alaswad, Garcia – Perez A, et al.
International Journal of Hydrogen Energy (2022) Vol. 48, Iss. 1, pp. 291-303
Open Access | Times Cited: 46
Degradation prediction of proton exchange membrane fuel cell based on Bi-LSTM-GRU and ESN fusion prognostic framework
Songyang Li, Weiling Luan, Chang Wang, et al.
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 78, pp. 33466-33478
Closed Access | Times Cited: 44
Durability estimation and short-term voltage degradation forecasting of vehicle PEMFC system: Development and evaluation of machine learning models
Ze Liu, Sichuan Xu, Honghui Zhao, et al.
Applied Energy (2022) Vol. 326, pp. 119975-119975
Closed Access | Times Cited: 41
Polymer electrolyte membrane fuel cells degradation prediction using multi-kernel relevance vector regression and whale optimization algorithm
Kui Chen, Abderrezak Badji, Salah Laghrouche, et al.
Applied Energy (2022) Vol. 318, pp. 119099-119099
Open Access | Times Cited: 39
Evolutionary gate recurrent unit coupling convolutional neural network and improved manta ray foraging optimization algorithm for performance degradation prediction of PEMFC
Zihan Tao, Chu Zhang, Jinlin Xiong, et al.
Applied Energy (2023) Vol. 336, pp. 120821-120821
Closed Access | Times Cited: 39
Weight optimized unscented Kalman filter for degradation trend prediction of lithium-ion battery with error compensation strategy
Yong Zhang, Lei Tu, Zhiwei Xue, et al.
Energy (2022) Vol. 251, pp. 123890-123890
Closed Access | Times Cited: 38
Progress in prediction of remaining useful life of hydrogen fuel cells based on deep learning
Wenbin He, Ting Liu, Wuyi Ming, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 192, pp. 114193-114193
Closed Access | Times Cited: 27
Performance degradation prediction method of PEM fuel cells using bidirectional long short-term memory neural network based on Bayesian optimization
Dongfang Chen, Wenlong Wu, Kuanyu Chang, et al.
Energy (2023) Vol. 285, pp. 129469-129469
Closed Access | Times Cited: 23
A novel WaveNet-GRU deep learning model for PEM fuel cells degradation prediction based on transfer learning
Mohammad J. Izadi, Pourya Hassani, Mehrdad Raeesi, et al.
Energy (2024) Vol. 293, pp. 130602-130602
Closed Access | Times Cited: 13
Fuel cell life prediction considering the recovery phenomenon of reversible voltage loss
Xuan Meng, Chuanyu Sun, Jian Mei, et al.
Journal of Power Sources (2024) Vol. 625, pp. 235634-235634
Closed Access | Times Cited: 13
Application of artificial intelligence in the materials science, with a special focus on fuel cells and electrolyzers
Mariah Batool, Oluwafemi Joseph Sanumi, Jasna Janković
Energy and AI (2024) Vol. 18, pp. 100424-100424
Open Access | Times Cited: 11
Transfer learning-based deep learning models for proton exchange membrane fuel remaining useful life prediction
Getnet Awoke Kebede, Shih‐Che Lo, Fu‐Kwun Wang, et al.
Fuel (2024) Vol. 367, pp. 131461-131461
Closed Access | Times Cited: 10
A model with high-precision on proton exchange membrane fuel cell performance degradation prediction based on temporal convolutional network-long short-term memory
Chongyang Tu, Fen Zhou, Mu Pan
International Journal of Hydrogen Energy (2024) Vol. 74, pp. 414-422
Closed Access | Times Cited: 9
Accuracy improvement of fuel cell prognostics based on voltage prediction
Chang Liu, Jiabin Shen, Zhen Dong, et al.
International Journal of Hydrogen Energy (2024) Vol. 58, pp. 839-851
Open Access | Times Cited: 8
Remaining Useful Life Prediction for Fuel Cell Based on Support Vector Regression and Grey Wolf Optimizer Algorithm
Kui Chen, Salah Laghrouche, Abdesslem Djerdir
IEEE Transactions on Energy Conversion (2021) Vol. 37, Iss. 2, pp. 778-787
Closed Access | Times Cited: 44
Deep Learning Based Emotion Recognition and Visualization of Figural Representation
Xiaofeng Lu
Frontiers in Psychology (2022) Vol. 12
Open Access | Times Cited: 32
An evolutionary stacked generalization model based on deep learning and improved grasshopper optimization algorithm for predicting the remaining useful life of PEMFC
Chu Zhang, Haowen Hu, Jie Ji, et al.
Applied Energy (2022) Vol. 330, pp. 120333-120333
Closed Access | Times Cited: 31
An LSTM and ANN Fusion Dynamic Model of a Proton Exchange Membrane Fuel Cell
Wei Li, Xinli Wang, Lei Wang, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 19, Iss. 4, pp. 5743-5751
Closed Access | Times Cited: 27
Performance degradation decomposition-ensemble prediction of PEMFC using CEEMDAN and dual data-driven model
Changzhi Li, Wei Lin, Hangyu Wu, et al.
Renewable Energy (2023) Vol. 215, pp. 118913-118913
Open Access | Times Cited: 20
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