Equipment Fault Prognosis Based on Temporal Association Rules
Equipment fault prognosis is important for reliability, operational safety, and efficient performance of equipment. Temporal fault data model is built according to the principles of the Apriori traditional association rules algorithm based on the characteristics of fault data. An Improved Apriori al...
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| Main Authors: | , , , , |
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| Format: | EJournal Article |
| Published: |
Institute of Advanced Engineering and Science,
2014-03-01.
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| Subjects: | |
| Online Access: | Get fulltext |
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