High precision implicit function learning for forecasting supercapacitor state of health based on Gaussian process regression

State of health (SOH) prediction of supercapacitors aims to provide reliable lifetime control and avoid system failure. Gaussian process regression (GPR) has emerged for SOH prediction because of its capability of capturing nonlinear relationships between features, and tracking SOH attenuations effe...

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Detalles Bibliográficos
Autores principales: Ren, Jiahao, Cai, Junfei, Li, Jinjin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187390/
https://www.ncbi.nlm.nih.gov/pubmed/34103569
http://dx.doi.org/10.1038/s41598-021-91241-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187390/
https://www.ncbi.nlm.nih.gov/pubmed/34103569
http://dx.doi.org/10.1038/s41598-021-91241-z

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