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LSTM-based failure prediction for railway rolling stock equipment.

Luigi De SimoneEnzo CaputoMarcello CinqueAntonio GalliVincenzo MoscatoStefano RussoGuido CesaroVincenzo CriscuoloGiuseppe Giannini
Published in: Expert Syst. Appl. (2023)
Keyphrases
  • failure prediction
  • stock market
  • recurrent neural networks
  • stock price
  • stock trading
  • traffic management
  • stock data
  • mathematical model
  • tool wear
  • machine learning
  • multiscale
  • fault diagnosis