Refining the Optimization Target for Automatic Univariate Time Series Anomaly Detection in Monitoring Services

no code implementations • 20 Jul 2023 • Manqing Dong, Zhanxiang Zhao, Yitong Geng, Wentao Li, Wei Wang, Huai Jiang

Time series anomaly detection is crucial for industrial monitoring services that handle a large volume of data, aiming to ensure reliability and optimize system performance.

Anomaly Detection Time Series +1

Ymir: A Supervised Ensemble Framework for Multivariate Time Series Anomaly Detection

no code implementations • 9 Dec 2021 • Zhanxiang Zhao

We proposed a multivariate time series anomaly detection frame-work Ymir, which leverages ensemble learning and supervisedlearning technology to efficiently learn and adapt to anomaliesin real-world system applications.

Ensemble Learning Time Series +2