Remaining Useful Life Estimation for Prognostics of Lithium-Ion Batteries Based on Recurrent Neural Network. Catelani, M., Ciani, L., Fantacci, R., Patrizi, G., & Picano, B. IEEE Trans. Instrum. Meas., 70:1–11, 2021. Paper doi bibtex @article{DBLP:journals/tim/CatelaniCFPP21,
author = "Catelani, Marcantonio and Ciani, Lorenzo and Fantacci, Romano and Patrizi, Gabriele and Picano, Benedetta",
title = "Remaining Useful Life Estimation for Prognostics of Lithium-Ion Batteries Based on Recurrent Neural Network",
journal = "{IEEE} Trans. Instrum. Meas.",
volume = "70",
pages = "1--11",
year = "2021",
url = "https://doi.org/10.1109/TIM.2021.3111009",
doi = "10.1109/TIM.2021.3111009",
timestamp = "Tue, 05 Oct 2021 01:00:00 +0200",
biburl = "https://dblp.org/rec/journals/tim/CatelaniCFPP21.bib",
bibsource = "dblp computer science bibliography, https://dblp.org"
}
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