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An enhanced neural network model for predicting the remaining useful life of proton exchange membrane fuel cells

Abstract In this study, a GMA based approach to predict proton exchange membrane fuel cell (PEMFC) stack voltage and remaining useful life (RUL) was proposed, and how different combinations of input and output sizes affect model performance was analyzed. The results show that the GMA model effective...

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Hlavní autoři: Honghua Pan, Yujin Zou, Xiao Sun, Jun Fu
Médium: Artigo
Jazyk:Inglês
Vydáno: Nature Portfolio 2025-10-01
Edice:Scientific Reports
Témata:
PEMFC
RUL prediction
GMA model
Enhanced neural network model
On-line přístup:https://doi.org/10.1038/s41598-025-21247-4
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