DTS-MixNet: Dynamic Spatiotemporal Graph Mixed Network for Anomaly Detection in Multivariate Time Series

Anomaly detection in multivariate time series (MTS) remains challenging due to the presence of complex and dynamic spatiotemporal dependencies. To address this, we propose the <i>Dynamic Spatiotemporal Graph Mixed Network</i> (DTS-MixNet), which takes a sliding window data as input to predict the ne...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Chengxun Tan, Jiayi Hu, Jian Li, Minmin Miao, Wenjun Hu, Shitong Wang
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2025-09-01
Sarja:	Big Data and Cognitive Computing
Aiheet:	multivariate time series anomaly detection graph neural networks spatiotemporal dependencies dynamic graph learning
Linkit:	https://www.mdpi.com/2504-2289/9/10/245
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