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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:

State of Health estimation for lithium-ion batteries using Random Forest and Gated Recurrent Unit
Xiaojuan Wang, Bing Hu, Xin Su, et al.
Journal of Energy Storage (2023) Vol. 76, pp. 109796-109796
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

High-Throughput Screening of 6858 Compounds for Zinc-Ion Battery Cathodes via Hybrid Machine Learning Optimization
Y.S. Wudil, M.A. Gondal, Mohammed A. Al‐Osta
ACS Applied Materials & Interfaces (2025)
Closed Access | Times Cited: 2
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 | Times Cited: 1
A novel hybrid neural network-based SOH and RUL estimation method for lithium-ion batteries
Baoliang Chen, Yonggui Liu, Bin Xiao
Journal of Energy Storage (2024) Vol. 98, pp. 113074-113074
Closed Access | Times Cited: 8
Applications of Long Short-Term Memory (LSTM) Networks in Polymeric Sciences: A Review
Ivan Malashin, В С Тынченко, Andrei Gantimurov, et al.
Polymers (2024) Vol. 16, Iss. 18, pp. 2607-2607
Open Access | Times Cited: 6
Aging abnormality detection of lithium-ion batteries combining feature engineering and deep learning
Jingcai Du, Caiping Zhang, Shuowei Li, et al.
Energy (2024) Vol. 297, pp. 131276-131276
Closed Access | Times Cited: 5
A comprehensive review of state-of-charge and state-of-health estimation for lithium-ion battery energy storage systems
Junjie Tao, Shunli Wang, Wen Cao, et al.
Ionics (2024) Vol. 30, Iss. 10, pp. 5903-5927
Closed Access | Times Cited: 5
State of health estimation of lithium-ion battery during fast charging process based on BiLSTM-Transformer
Ziyang Li, Xiangwen Zhang, Wei Gao
Energy (2024) Vol. 311, pp. 133418-133418
Closed Access | Times Cited: 5
State of Health Estimation and Battery Management: A Review of Health Indicators, Models and Machine Learning
Mei Li, Wenting Xu, Shiwen Zhang, et al.
Materials (2025) Vol. 18, Iss. 1, pp. 145-145
Open Access
A Deep Learning Multi-Feature Based Fusion Model for Predicting the State of Health of Lithium-Ion Batteries
Ankit Sonthalia, Femilda Josephin JS, Edwin Geo Varuvel, et al.
Energy (2025), pp. 134569-134569
Closed Access
A supercritical carbon dioxide cooling heat transfer machine learning prediction model based on direct numerical simulation
Dingchen Wu, Mingshan Wei, Ran Tian, et al.
International Communications in Heat and Mass Transfer (2025) Vol. 163, pp. 108753-108753
Closed Access
Random Forest-Based Grouping for Accurate SOH Estimation in Second-Life Batteries
Joelton Deonei Gotz, José Rodolfo Galvão, Fernanda Cristina Corrêa, et al.
Vehicles (2024) Vol. 6, Iss. 2, pp. 799-813
Open Access | Times Cited: 4
Refined lithium-ion battery state of health estimation with charging segment adjustment
Kun Zheng, Jinhao Meng, Zhipeng Yang, et al.
Applied Energy (2024) Vol. 375, pp. 124077-124077
Closed Access | Times Cited: 4
Enhanced battery health monitoring in electric vehicles: A novel hybrid HBA-HGBR model
Wenjun Liao, Zilong Chen, Pingfei Li, et al.
Journal of Energy Storage (2025) Vol. 110, pp. 115316-115316
Closed Access
Jointed SOH Estimation of Electric Bus Batteries Based on Operating Conditions and Multiple Indicators
Xiaohui Xu, Ke Deng, Jibin Yang, et al.
Sustainability (2025) Vol. 17, Iss. 3, pp. 812-812
Open Access
State of health estimation for lithium-ion batteries based on fragmented charging data and improved gated recurrent unit neural network
Zheng Chen, Peng Yue, Jiangwei Shen, et al.
Journal of Energy Storage (2025) Vol. 115, pp. 115952-115952
Closed Access
Lithium batteries health state prediction method based on TCN-GRU-Attention fusion model with multi-source charging information
Yong Liu, Sangyu Lai, Yujiao Mai, et al.
AIP Advances (2025) Vol. 15, Iss. 2
Open Access
Lithium-Ion Battery State of Health Estimation Based on Feature Reconstruction and Transformer-GRU Parallel Architecture
Bing Chen, Yongjun Zhang, Jinsong Wu, et al.
Energies (2025) Vol. 18, Iss. 5, pp. 1236-1236
Open Access
Deep Learning for State of Health Estimation of Lithium-Ion Batteries in Electric Vehicles: A Systematic Review
Chenyuan Liu, Heng Li, Kexin Li, et al.
Energies (2025) Vol. 18, Iss. 6, pp. 1463-1463
Open Access
Random Forest-Based Machine Learning Model Design for 21,700/5 Ah Lithium Cell Health Prediction Using Experimental Data
Sid-Ali Amamra
Physchem (2025) Vol. 5, Iss. 1, pp. 12-12
Open Access
State of health estimation for lithium-ion batteries based on optimal feature subset algorithm
Jing Sun, Haitao Wang
Energy (2025), pp. 135685-135685
Closed Access
High-accuracy state-of-charge fusion estimation of lithium-ion batteries by integrating the Extended Kalman Filter with feature-enhanced Random Forest
Zhihui Zhao, Farong Kou, Zhengniu Pan, et al.
Journal of Energy Storage (2025) Vol. 118, pp. 116275-116275
Closed Access
A physics-informed neural network-based method for predicting degradation trajectories and remaining useful life of supercapacitors
E Lixin, Jun Wang, Ruixin Yang, et al.
Green Energy and Intelligent Transportation (2025), pp. 100291-100291
Open Access
Lithium-ion battery state of health estimation method based on variational quantum algorithm optimized stacking strategy
Longze Wang, Siyu Jiang, Yuteng Mao, et al.
Energy Reports (2024) Vol. 11, pp. 2877-2891
Open Access | Times Cited: 3
Improved Deep Extreme Learning Machine for State of Health Estimation of Lithium-Ion Battery
Yan Chen, Junli Meng, Shunyang Ming, et al.
International Journal of Energy Research (2024) Vol. 2024, pp. 1-22
Open Access | Times Cited: 2
A Robust Multi-Model Framework for Groundwater Level Prediction: The BFSA-MVMD-GRU-RVM Model
Akram Seifi, Sharareh Pourebrahim, Mohammad Ehteram, et al.
Results in Engineering (2024), pp. 103250-103250
Open Access | Times Cited: 2
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