Sparse Autoencoded Long Short-Term Memory Network for State-of-Charge Estimations
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/9490020/9490033/09490070.pdf?arnumber=9490070
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. State-of-Health Forecasting for Battery Cells using Bayesian Inference and LSTM-based Change Point Detection;2023 IEEE Energy Conversion Congress and Exposition (ECCE);2023-10-29
2. Orthogonal Autoencoders for Long-Term State-of-Charge Forecasting of Li-ion Battery Cells;2023 IEEE Transportation Electrification Conference & Expo (ITEC);2023-06-21
3. A Novel Neural Network With Gaussian Process Feedback for Modeling the State-of-Charge of Battery Cells;IEEE Transactions on Industry Applications;2022-07
4. A Polynomial Regression Model with Bayesian Inference for State-of-Health Prediction of Li-ion Batteries;2022 IEEE Transportation Electrification Conference & Expo (ITEC);2022-06-15
5. Uncorrelated Sparse Autoencoder With Long Short-Term Memory for State-of-Charge Estimations in Lithium-Ion Battery Cells;IEEE Transactions on Automation Science and Engineering;2022
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