TSAD: Temporal–spatial association differences-based unsupervised anomaly detection for multivariate time-series

Hanbing Zhu; Nan Xiao; Hefei Ling; Zongyi Li; Yuxuan Shi; Chuang Zhao; Hongxu Ji; Ping Li; Hui Liu

doi:10.1016/j.neucom.2025.130611

ScienceGate Book Chapters

JOURNAL ARTICLE

TSAD: Temporal–spatial association differences-based unsupervised anomaly detection for multivariate time-series

Hanbing Zhu Nan Xiao Hefei Ling Zongyi Li Yuxuan Shi Chuang Zhao Hongxu Ji Ping Li Hui Liu

Year: 2025 Journal: Neurocomputing Vol: 648 Pages: 130611-130611 Publisher: Elsevier BV

DOI: 10.1016/j.neucom.2025.130611

Get Full-Text PDF Get Analytical Report

Keywords:

Multivariate statistics Anomaly detection Series (stratigraphy) Time series Computer science Anomaly (physics) Artificial intelligence Association (psychology) Pattern recognition (psychology) Data mining Machine learning Geology Psychology

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.08

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Time Series Analysis and Forecasting

Physical Sciences → Computer Science → Signal Processing

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

TSAD: Temporal–spatial association differences-based unsupervised anomaly detection for multivariate time-series

Metrics

Topics

Related Documents

Spatial-Temporal Interaction Decoding Transformer for Unsupervised Multivariate Time Series Anomaly Detection

VGG Based Unsupervised Anomaly Detection in Multivariate Time Series

FedSW-TSAD: SWGAN-Based Federated Time Series Anomaly Detection

Spatial-Temporal Dependency Based Multivariate Time Series Anomaly Detection for Industrial Processes

Skip-patching spatial–temporal discrepancy-based anomaly detection on multivariate time series