Medical rolling bearing fault prognostics based on improved extreme learning machine

DOI10.1007/s10878-019-00494-yOpenAlexW2990823512MaRDI QIDQ2060047

Yang Wu, Ying Xu, Chein-Shan Liu, Tao Wu, Cheng He, Tong Chen

Publication date: 13 December 2021

Published in: Journal of Combinatorial Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10878-019-00494-y

zbMATH Keywords

accuracy rateensemble error minimized extreme learning machinefault prognosticsmedical rolling bearingVMD

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Deterministic scheduling theory in operations research (90B35) Stochastic scheduling theory in operations research (90B36)

Cites Work

• Special issue for FAW 2014
• Supply chain scheduling problem in the hospital with periodic working time on a single machine
• Prioritized surgery scheduling in face of surgeon tiredness and fixed off-duty period
• Trends in extreme learning machines: a review
• Online scheduling on bounded batch machines to minimize the maximum weighted completion time
• Variational Mode Decomposition

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