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Record #72070

A hybrid LSTM random forest model with grey wolf optimization for enhanced detection of multiple bearing faults

Original paper date
Oct 14, 2024
Institution
Department of Mechanical Engineering, University of Chlef, Ouled Fares, Algeria · SIME Laboratory, University of Tunis, ENSIT, Tunis, Tunisia · LGEM Laboratory, Faculty of Technology, University of Batna 2, Batna, Algeria · LGMM Laboratory, Faculty of Technology, University of 20 August 1955, Skikda, Algeria · Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun, 248002, India · Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan · College of Engineering, University of Business and Technology, Jeddah, 21448, Saudi Arabia · Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, 03680, Ukraine · Center for Information-Analytical and Technical Support of Nuclear Power Facilities Monitoring, National Academy of Sciences of Ukraine, Akademika Palladina Avenue, 34-A, Kyiv, Ukraine
Open access
No
Article type
Research Article
Broad categories
(B/T) Computer Science(PHY) Engineering - Structural
Notes from Retraction Watch

See also: https://pubpeer.com/publications/CC68AB081D6C944503C8398649BB82

Citation lifecycle

How this paper is being cited

Pre-retraction
47
Same day
0
Post-retraction
0
% post-retraction
0.0%
~28.5 citations/yr before retraction
— citing papers

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