Open AccessAnomaly Detection Using LSTM-Autoencoder to Predict Coal Pulverizer Condition on Coal-Fired Power Plant
Author(s) -
Henry Pariaman,
Gita Maya Luciana,
Muhammad Kamal Wisyaldin,
Muhammad Hisjam
Publication year - 2021
Publication title -
evergreen
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.378
H-Index - 11
eISSN - 2432-5953
pISSN - 2189-0420
DOI - 10.5109/4372264
Subject(s) - autoencoder , pulverizer , coal , anomaly detection , anomaly (physics) , power (physics) , environmental science , coal fired power plant , power station , artificial intelligence , waste management , computer science , engineering , artificial neural network , electrical engineering , grinding , mechanical engineering , physics , quantum mechanics , condensed matter physics
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