Autonomous anomaly detection for streaming data
Anomaly detection from data streams is a hotly studied topic in the machine learning domain. It is widely considered a challenging task because the underlying patterns exhibited by the streaming data may dynamically change at any time. In this paper, a new algorithm is proposed to detect anomalies a...
| Published in: | KNOWLEDGE-BASED SYSTEMS |
|---|---|
| Main Authors: | , , , , , , , |
| Format: | Article; Early Access |
| Language: | English |
| Published: |
ELSEVIER
2024
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| Subjects: | |
| Online Access: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001133574000001 |