Learning-Aided Life Cycle Prediction of Batteries in Data Centers-Reference-Cited by-同舟云学术

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Learning-Aided Life Cycle Prediction of Batteries in Data Centers

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Smart Electrical Grid and Renewable Energy (SEGRE)
language:
Short-container-title:

Author:

Zhang Ziting¹,Chi Xiaoyu²,Wang Tao³,Meng Rui²,Jin Liang⁴,Zeng Yu¹

Affiliation:

1. China Telecom Research Institute,AI Research Centre,Beijing,China

2. Beijing University of Posts and Telecommunications,Beijing,China

3. Big Data and AI Center,China Telecom Corporation Limited

4. Beijing University of Posts and Telecommunications,Big Data and AI Center,Beijing,China

Funder

Research and Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10269161/10269234/10269255.pdf?arnumber=10269255

Reference15 articles.

1. A Data-Driven Approach With Uncertainty Quantification for Predicting Future Capacities and Remaining Useful Life of Lithium-ion Battery

2. Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

3. Zeroth-order supervised policy improvement[J];sun,2020

4. Safe exploration by solving early terminated mdp[J];sun,2021

5. The early prediction of lithium-ion battery remaining useful life using a novel Long Short-Term Memory network

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