Deep learning-based vehicular engine health monitoring system utilising a hybrid convolutional neural network/bidirectional gated recurrent unit
Vehicles play a pivotal role in the current era of Industry 4.0 by providing passengers with excellent mobility, comfort, and safety while strengthening national and international economies. Unanticipated vehicular engine issues can hinder performance and lead to costly maintenance. As analytics pro...
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Main Authors: | , , , , , |
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Format: | Article |
Language: | English English |
Published: |
Elsevier
2024
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Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/42480/1/Deep%20learning-based%20vehicular%20engine%20health%20monitoring%20system_ABST.pdf http://umpir.ump.edu.my/id/eprint/42480/2/Deep%20learning-based%20vehicular%20engine%20health%20monitoring%20system.pdf http://umpir.ump.edu.my/id/eprint/42480/ https://doi.org/10.1016/j.eswa.2024.125080 https://doi.org/10.1016/j.eswa.2024.125080 |
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http://umpir.ump.edu.my/id/eprint/42480/1/Deep%20learning-based%20vehicular%20engine%20health%20monitoring%20system_ABST.pdfhttp://umpir.ump.edu.my/id/eprint/42480/2/Deep%20learning-based%20vehicular%20engine%20health%20monitoring%20system.pdf
http://umpir.ump.edu.my/id/eprint/42480/
https://doi.org/10.1016/j.eswa.2024.125080
https://doi.org/10.1016/j.eswa.2024.125080