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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| 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 |