Deep Learning Approaches to RUL Prediction of Lithium-ion Batteries
Author:
Funder
Agency for Defense Developmen
Publisher
The Korean Society of Manufacturing Process Engineers
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. Predicting the RUL of Li-Ion Batteries in UAVs Using Machine Learning Techniques;Computers;2024-02-29
2. Design and Implementation of Platform for Small-Scale Smart Farm using Deep Learning;Journal of the Korean Society of Manufacturing Process Engineers;2023-11-30
3. Development of an LCD 3D Printer Process Parameter Recommendation System by Machine Learning;Journal of the Korean Society of Manufacturing Technology Engineers;2023-04-15
4. Lithium-ion battery RUL prediction using ANN and comparison to alternative models;2022 IEEE North Karnataka Subsection Flagship International Conference (NKCon);2022-11-20
5. Artificial Intelligence-based Battery State-of-Health (SoH) Prediction through battery data characteristics analysis;2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS);2022-05-02
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