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Application of Electrochemical Impedance Spectroscopy for prediction of Fuel Cell degradation by LSTM neural networks.
Riccardo Caponetto
Nicola Guarnera
Fabio Matera
Emanuela Privitera
Maria Grazia Xibilia
Published in:
MED (2021)
Keyphrases
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neural network
prediction accuracy
fuel cell
recurrent neural networks
artificial intelligence
social networks
information systems
artificial neural networks
fuzzy logic
data sets
decision trees
computational intelligence
neural network ensemble