Unsupervised spatio-temporal state estimation for fine-grained anomaly diagnosis of cyber-physical systems

To reveal the spatio-temporal dependence and evolution mechanisms in cyber-physical system operational states, a fine-grained adaptive multivaviate time series anomaly diagnosis (MAD-Transformer) model was proposed for identifying and diagnosing anomalies in multivariate time series (MTS). MAD-Trans...

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Bibliographic Details
Main Authors: SUN Haili, HUANG Yan, HAN Lansheng, ZHOU Chunjie
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2025-07-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2025129/
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