Anomaly Detection for Multivariate Time Series with Multi-scale Feature Interactions

Fulu Kou; Lixing Yu; Kun Yue; Liang Duan; Zhongbin Li

doi:10.1007/978-981-97-5569-1_30

ScienceGate Book Chapters

BOOK-CHAPTER

Anomaly Detection for Multivariate Time Series with Multi-scale Feature Interactions

Fulu Kou Lixing Yu Kun Yue Liang Duan Zhongbin Li

Year: 2024 Lecture notes in computer science Pages: 459-475 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-97-5569-1_30

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Anomaly detection Series (stratigraphy) Multivariate statistics Scale (ratio) Feature (linguistics) Time series Anomaly (physics) Artificial intelligence Pattern recognition (psychology) Data mining Machine learning Cartography Geology Geography

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.52

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Time Series Analysis and Forecasting

Physical Sciences → Computer Science → Signal Processing

Anomaly Detection for Multivariate Time Series with Multi-scale Feature Interactions

Metrics

Topics

Related Documents

Probabilistic autoencoder with multi-scale feature extraction for multivariate time series anomaly detection

HIFI: Anomaly Detection for Multivariate Time Series with High-order Feature Interactions

A robust multi-scale feature extraction framework with dual memory module for multivariate time series anomaly detection

Hfn:Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection

A Multi-scale Parallel Unsupervised Model for Multivariate Time Series Anomaly Detection