Remaining useful life prediction for rotating machinery using bidirectional LSTM: a comparative deep learning study

Life Cycle Reliability and Safety Engineering 2026

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Authors: A. Ghavidel, H. Park, S. Kovacic, A. Souza-Poza
DOI: 10.1007/s41872-026-00406-0
Cited by: 1
References: 17

Fields of Study & Subjects

Machine Fault Diagnosis Techniques Metallurgy and Material Forming Financial Distress and Bankruptcy Prediction

Publication details

Journal / source
Life Cycle Reliability and Safety Engineering
Publisher
Springer Science and Business Media LLC
Publication date
30 March 2026
Language
EN