A data mining approach for fault diagnosis: An application of anomaly detection algorithm
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Purarjomandlangrudi, Afrooz 
ORCID: https://orcid.org/0000-0003-3028-1408, Ghapanchi, Amir ORCID: https://orcid.org/0000-0002-1897-0748 and Esmalifalak, M
(2014)
A data mining approach for fault diagnosis: An application of anomaly detection algorithm.
Measurement, 55.
343 - 352.
ISSN 0263-2241
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| Item type | Article |
| URI | https://vu-9.eprints-hosting.org/id/eprint/35581 |
| DOI | 10.1016/j.measurement.2014.05.029 |
| Official URL | https://www.sciencedirect.com/science/article/pii/... |
| Subjects | Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing Current > Division/Research > College of Science and Engineering |
| Keywords | defects; algorithms; SVM; support vector machine |
| Citations in Scopus | 95 - View on Scopus |
| Download/View statistics | View download statistics for this item |
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