Zi-Qiu Nie

A hybrid rule-learning framework for identifying anomalies in high-frequency groundwater-level data.

High-frequency groundwater monitoring is critical for effective water-resource management, yet anomaly identification in high-frequency monitoring data remains challenging because of strong temporal variability, heterogeneous regional characteristics, and diverse anomaly patterns. In this study, we proposed a hybrid ru...