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Recurrent Neural Networks for Fault Detection: An exploratory study on a dataset about air compressor failures of heavy duty trucks
Chen, Kunru
Halmstad University, School of Information Technology.
2018 (English)
Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE credits
Student thesis
Place, publisher, year, edition, pages
2018.
Keywords [en]
Predictive Maintenance, LSTM, Fault Detection
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN:
urn:nbn:se:hh:diva-38184
OAI: oai:DiVA.org:hh-38184
DiVA, id:
diva2:1257115
Educational program
Master's Programme in Information Technology, 120 credits
Available from:
2018-10-24
Created:
2018-10-18
Last updated:
2018-10-24
Bibliographically approved
Open Access in DiVA
fulltext
(8684 kB)
221 downloads
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FULLTEXT02.pdf
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8684 kB
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3e770517d4f7e54f12a88da1955bee80700678986d26e156c0c570d078b1e5501d48defae1e483a41c4e456ae12796ad47376ed6b005d21f254f1bb07e128775
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fulltext
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School of Information Technology
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Other Electrical Engineering, Electronic Engineering, Information Engineering
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Total: 221 downloads
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harvard1
ieee
modern-language-association-8th-edition
vancouver
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harvard1
ieee
modern-language-association-8th-edition
vancouver
Other style
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de-DE
en-GB
en-US
fi-FI
nn-NO
nn-NB
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