Litcius/Paper detail

Unsupervised anomaly detection in hourly water demand data using an asymmetric encoder–decoder model

Jieru Yan, Tao Tao

2022Journal of Hydrology10 citationsDOI

Topics & Concepts

Anomaly detectionAutoencoderComputer scienceOutlierAnomaly (physics)SIGNAL (programming language)Upstream (networking)Data miningFeature (linguistics)Pattern recognition (psychology)Environmental scienceArtificial intelligenceDeep learningTelecommunicationsPhilosophyLinguisticsProgramming languageCondensed matter physicsPhysicsWater Systems and OptimizationAnomaly Detection Techniques and ApplicationsHydrology and Drought Analysis
Unsupervised anomaly detection in hourly water demand data using an asymmetric encoder–decoder model | Litcius