Contrastive learning for practical battery synthetic data generation using seasonal and trend representations-Reference-Cited by-同舟云学术

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Contrastive learning for practical battery synthetic data generation using seasonal and trend representations

Published:2022-09 Issue:15 Volume:46 Page:24602-24610
ISSN:0363-907X
Container-title:International Journal of Energy Research
language:en
Short-container-title:Intl J of Energy Research

Author:

Gowda Hruday¹,Channegowda Janamejaya¹^ORCID

Affiliation:

1. Department of Electrical and Electronics Engineering M.S. Ramaiah Institute of Technology Bengaluru India

Publisher

Hindawi Limited

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.8651

Reference51 articles.

1. Mini Grids for Half a Billion People

2. Critical review of on-board capacity estimation techniques for lithium-ion batteries in electric and hybrid electric vehicles

3. Critical review of state of health estimation methods of Li-ion batteries for real applications

4. Towards a smarter battery management system: A critical review on battery state of health monitoring methods

Cited by 2 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. Generating synthetic energy time series: A review;Renewable and Sustainable Energy Reviews;2024-12

2. Decomposition-based Data Augmentation for Time-series Building Load Data;Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation;2023-11-15

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