Improved principal component analysis for anomaly detection: Application to an emergency department
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- 作者：Fouzi Harroua ; fouzi.harrou1@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Farid Kadrib ; farid.kadri@univ-valenciennes.fr" class="auth_mail" title="E-mail the corresponding author ; Sondes Chaabaneb ; sondes.chaabane@univ-valenciennes.fr" class="auth_mail" title="E-mail the corresponding author ; Christian Tahonb ; christian.tahon@univ-valenciennes.fr" class="auth_mail" title="E-mail the corresponding author ; Ying Suna ; ying.sun@kaust.edu.sa" class="auth_mail" title="E-mail the corresponding author
- 关键词：Statistical anomaly detection ; Multivariate CUSUM ; Emergency department ; Abnormal situation
- 刊名：Computers & Industrial Engineering
- 出版年：2015
- 出版时间：October 2015
- 年：2015
- 卷：88
- 期：Complete
- 页码：63-77
- 全文大小：2020 K
文摘
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Developed PCA-based MCUSUM anomaly detection (AD) method.
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Extended the AD advantages of the MCUSUM to enhance the conventional PCA.
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The proposed algorithm is applied to monitor an emergency department.
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The detection results show effectiveness of the proposed method.