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Anomaly detection in non-stationary data: ensemble based self-adaptive OCSVM

Ghafoori, Zahra, Erfani, Sarah M., Rajasegarar, Sutharshan, Karunasekera, Shanika and Leckie, Christopher A. 2016, Anomaly detection in non-stationary data: ensemble based self-adaptive OCSVM, in IJCNN 2016: Proceedings of the IEEE International Joint Conference on Neural Networks, IEEE, Piscataway, N.J., pp. 2476-2483, doi: 10.1109/IJCNN.2016.7727507.

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Title Anomaly detection in non-stationary data: ensemble based self-adaptive OCSVM
Author(s) Ghafoori, Zahra
Erfani, Sarah M.
Rajasegarar, Sutharshan
Karunasekera, Shanika
Leckie, Christopher A.
Conference name IEEE International Joint Conference on Neural Networks (2016 : Vancouver, Canada)
Conference location Vancouver, Canada
Conference dates 24-29 Jul. 2016
Title of proceedings IJCNN 2016: Proceedings of the IEEE International Joint Conference on Neural Networks
Publication date 2016
Conference series IEEE International Joint Conference on Neural Networks
Start page 2476
End page 2483
Total pages 8
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) WIRELESS SENSOR NETWORKS
ISBN 9781509006205
Language eng
DOI 10.1109/IJCNN.2016.7727507
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890299 Computer Software and Services not elsewhere classified
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2016, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30090705

Document type: Conference Paper
Collection: School of Information Technology
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