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...
出版年: | KNOWLEDGE-BASED SYSTEMS |
---|---|
主要な著者: | , , , , , , , |
フォーマット: | Article; Early Access |
言語: | English |
出版事項: |
ELSEVIER
2024
|
主題: | |
オンライン・アクセス: | https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001133574000001 |