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Data-Driven Prognostics of the SOFC System Based on Dynamic Neural Network Models

Prognostics technology is important for the sustainability of solid oxide fuel cell (SOFC) system commercialization, i.e., through failure prevention, reliability assessment, and the remaining useful life (RUL) estimation. To solve SOFC system issues, data-driven prognostics methods based on the dyn...

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Autors principals: Shan-Jen Cheng, Wen-Ken Li, Te-Jen Chang, Chang-Hung Hsu
Format: Artigo
Idioma:Inglês
Publicat: MDPI AG 2021-09-01
Col·lecció:Energies
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Accés en línia:https://www.mdpi.com/1996-1073/14/18/5841
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