A conditional random field based feature learning framework for battery capacity prediction

This paper proposes a network model framework based on long and short-term memory (LSTM) and conditional random field (CRF) to promote Li-ion battery capacity prediction results. The model uses LSTM to extract temporal features from the data and CRF to build a transfer matrix to enhance temporal fea...

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Detalles Bibliográficos
Autores principales: Wang, Hai-Kun, Zhang, Yang, Huang, Mohong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345946/
https://www.ncbi.nlm.nih.gov/pubmed/35918374
http://dx.doi.org/10.1038/s41598-022-17455-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9345946/
https://www.ncbi.nlm.nih.gov/pubmed/35918374
http://dx.doi.org/10.1038/s41598-022-17455-x

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