AFMF: Time series anomaly detection framework with modified forecasting

Li Shen, Yuning Wei, Yangzhu Wang, Hongguang Li

Abstract: Highlights•Novel forecasting-based time series anomaly detection framework with three components.•Two components are evolved from existing methods but more considerate and powerful while the rest one is completely novel.•Better performances than fifteen baselines on ten benchmarks and diverse settings