Anomaly Data Detection

3 篇

Anomaly data detection aims to identify abnormal points in measurement data, which could be caused by sensor malfunctions, external interference, or data processing errors. In Structural Health Monitoring, detecting anomalous data is crucial for ensuring the reliability of analysis results. This category focuses on efficient algorithms that combine machine learning and statistical methods to distinguish normal and abnormal patterns from complex datasets.