Comparing LSTM and GRU Models to Predict the Condition of a Pulp Paper Press

Comparing LSTM and GRU Models to Predict the Condition of a Pulp Paper Press

The accuracy of a predictive system is critical for predictive maintenance and to support the right decisions at the right times. Statistical models, such as ARIMA and SARIMA, are unable to describe the stochastic nature of the data. Neural networks, such as long short-term memory (LSTM) and the gat...

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Bibliographic Details
Main Authors: Balduíno César Mateus, Mateus Mendes, José Torres Farinha, Rui Assis, António Marques Cardoso
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Energies
Subjects:
LSTM
recurrent neural network
GRU
paper press
predictive maintenance
Online Access:https://www.mdpi.com/1996-1073/14/21/6958

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https://www.mdpi.com/1996-1073/14/21/6958

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