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

Abstract 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 attenuat...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Jiahao Ren, Junfei Cai, Jinjin Li
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
R
Q
Acceso en línea:https://doaj.org/article/fb1468810a154f6aa8ac62e8237402a0
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!