- 专利标题: Anomaly detection in multidimensional time series data
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申请号: US15815057申请日: 2017-11-16
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公开(公告)号: US11157782B2公开(公告)日: 2021-10-26
- 发明人: Luis Angel D. Bathen , Simon-Pierre Genot , Mu Qiao , Ramani R. Routray
- 申请人: INTERNATIONAL BUSINESS MACHINES CORPORATION
- 申请人地址: US NY Armonk
- 专利权人: INTERNATIONAL BUSINESS MACHINES CORPORATION
- 当前专利权人: INTERNATIONAL BUSINESS MACHINES CORPORATION
- 当前专利权人地址: US NY Armonk
- 代理商 Robert R. Aragona
- 主分类号: G06K9/62
- IPC分类号: G06K9/62 ; G06N3/08 ; G06F17/15 ; G06N3/04 ; G06F17/17 ; G06K9/00
摘要:
A method, computer system, and computer program product to detect anomalies in a multivariate or multidimensional time series data set. The time series data set is retrieved from a monitored device. A pair of neural networks are trained simultaneously using the retrieved time series data set by implementing an adversarial training process, to generate a generative neural network and a discriminative neural network. The anomalies in the time series data set of the monitored device are detected by implementing one or both of the generative neural network and the discriminative neural network to monitor the time series data set.
公开/授权文献
- US20190147300A1 ANOMALY DETECTION IN MULTIDIMENSIONAL TIME SERIES DATA 公开/授权日:2019-05-16
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