Time Series Anomaly Detection

Time series anomaly detection refers to the process of identifying data points or subsequences that significantly deviate from normal patterns within time series data. Its goal is to promptly detect abnormal behaviors by analyzing historical data, thereby enabling early warnings and interventions. This technology has significant application value in fields such as financial risk control, industrial equipment maintenance, and cybersecurity monitoring, effectively enhancing the stability and security of systems.