CSCAD: Correlation Structure-Based Collective Anomaly Detection in Complex System

Detecting anomalies in large complex systems is a critical and challenging task. The difficulties arise from several aspects. First, collecting ground truth labels or prior knowledge for anomalies is hard in real-world systems, which often lead to limited or no anomaly labels in the dataset. Second,...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IEEE transactions on knowledge and data engineering Ročník 35; číslo 5; s. 4634 - 4645
Hlavní autori:	Qin, Huiling, Zhan, Xianyuan, Zheng, Yu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.05.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Anomalies Anomaly detection complex system Complex systems Correlation correlation mining Data models Datasets Feature extraction Labels Loss measurement Reconstruction Sensors unsupervised learning urban computing variational autoencoder
ISSN:	1041-4347, 1558-2191
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!