Anomaly Detection in Streaming Nonstationary Temporal Data
Work
Year: 2019
Type: article
Abstract: This article proposes a framework that provides early detection of anomalous series within a large collection of nonstationary streaming time-series data. We define an anomaly as an observation, that ... more
Authors Priyanga Dilini Talagala, Rob Hyndman, Kate Smith‐Miles, Sevvandi Kandanaarachchi, Mario Andrés Muñoz
Institutions ARC Centre of Excellence for Mathematical and Statistical Frontiers, Monash University, The University of Melbourne
Cites: 57
Cited by: 55
Related to: 10
FWCI: 5.911
Citation percentile (by year/subfield): 100
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Sustainable Development Goal Partnerships for the goals
Open Access status: green
Funder Australian Research Council
Grant ID LP160101885