MIM-GAN-based Anomaly Detection for Multivariate Time Series Data

The loss function of Generative adversarial network(GAN) is an important factor that affects the quality and diversity of the generated samples for anomaly detection. In this paper, we propose an unsupervised multiple time series anomaly detection algorithm based on the GAN with message importance m...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	arXiv.org 2023-10
Hauptverfasser:	Lu, Shan, Dong, Zhicheng, Cai, Donghong, Fang, Fang, Zhao, Dongcai
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Anomalies Generative adversarial networks Multivariate analysis Reconstruction Time series
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!