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...

詳細記述

書誌詳細
出版年:KNOWLEDGE-BASED SYSTEMS
主要な著者: Basheer, Muhammad Yunus Iqbal; Ali, Azliza Mohd; Hamid, Nurzeatul Hamimah Abdul; Ariffin, Muhammad Azizi Mohd; Osman, Rozianawaty; Nordin, Sharifalillah; Gu, Xiaowei
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