A space-embedding strategy for anomaly detection in multivariate time series
Anomaly detection of time series has always been a hot topic in academia and industry.
However, many existing multivariant time series methods suffer from common challenges …
However, many existing multivariant time series methods suffer from common challenges …
[HTML][HTML] Anomaly detection method for multivariate time series data of oil and gas stations based on digital twin and mtad-gan
Y Lian, Y Geng, T Tian - Applied Sciences, 2023 - mdpi.com
Due to the complexity of the oil and gas station system, the operational data, with various
temporal dependencies and inter-metric dependencies, has the characteristics of diverse …
temporal dependencies and inter-metric dependencies, has the characteristics of diverse …
A fast, decentralized covariance selection-based approach to detect cyber attacks in smart grids
Recent studies have shown that an attacker can compromise some of the power grid
measurements to mislead the conventional state estimators (SEs), since the manipulated …
measurements to mislead the conventional state estimators (SEs), since the manipulated …
Change detection in dynamic attributed networks
IU Hewapathirana - Wiley Interdisciplinary Reviews: Data …, 2019 - Wiley Online Library
A network provides powerful means of representing complex relationships between entities
by abstracting entities as vertices, and relationships as edges connecting vertices in a …
by abstracting entities as vertices, and relationships as edges connecting vertices in a …
Statistical structure learning to ensure data integrity in smart grid
H Sedghi, E Jonckheere - IEEE Transactions on Smart Grid, 2015 - ieeexplore.ieee.org
Robust control and management of the grid relies on accurate data. Both phasor
measurement units and remote terminal units are prone to false data injection attacks. Thus …
measurement units and remote terminal units are prone to false data injection attacks. Thus …
Detecting users' anomalous emotion using social media for business intelligence
Anomaly detection in sentiment analysis refers to detecting users' abnormal opinions,
sentiment patterns or special temporal aspects of such patterns. Users' emotional state …
sentiment patterns or special temporal aspects of such patterns. Users' emotional state …
Anomaly localization for network data streams with graph joint sparse PCA
Determining anomalies in data streams that are collected and transformed from various
types of networks has recently attracted significant research interest. Principal Component …
types of networks has recently attracted significant research interest. Principal Component …
Multi-task multi-modal models for collective anomaly detection
This paper proposes a new framework for anomaly detection when collectively monitoring
many complex systems. The prerequisite for condition-based monitoring in industrial …
many complex systems. The prerequisite for condition-based monitoring in industrial …
CONGO²: Scalable Online Anomaly Detection and Localization in Power Electronics Networks
Rapid and accurate detection and localization of electronic disturbances simultaneously are
important for preventing its potential damages and determining potential remedies. The …
important for preventing its potential damages and determining potential remedies. The …
Variable selection for kernel two-sample tests
We consider the variable selection problem for two-sample tests, aiming to select the most
informative variables to distinguish samples from two groups. To solve this problem, we …
informative variables to distinguish samples from two groups. To solve this problem, we …