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A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Purarjomandlangrudi, A, Ghapanchi, Amir ORCID: 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
Uncontrolled Keywords: defects; algorithms; SVM; support vector machine
Subjects: Current > FOR Classification > 0801 Artificial Intelligence and Image Processing
Current > Division/Research > College of Science and Engineering
Depositing User: Symplectic Elements
Date Deposited: 15 Feb 2018 03:24
Last Modified: 12 Mar 2018 22:50
URI: http://vuir.vu.edu.au/id/eprint/35581
DOI: https://doi.org/10.1016/j.measurement.2014.05.029
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Citations in Scopus: 54 - View on Scopus

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