Detecting Technical Anomalies in High-Frequency Water-Quality Data Using Artificial Neural Networks

Anomaly detection (AD) in high-volume environmental data requires one to tackle a series of challenges associated with the typical low frequency of anomalous events, the broad-range of possible anomaly types, and local nonstationary environmental conditions, suggesting the need for flexible statisti... View More