Drift-aware Anomaly Detection for Non-stationary Time Series
Author:
Affiliation:
1. Zhejiang University,Hangzhou,China
2. ZJU-Bangsun Joint Research Center,Hangzhou,China
Funder
Research and Development
Fundamental Research Funds for the Central Universities
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10385234/10386078/10386160.pdf?arnumber=10386160
Reference16 articles.
1. A Fuzzy Interval Time-Series Energy and Financial Forecasting Model Using Network-Based Multiple Time-Frequency Spaces and the Induced-Ordered Weighted Averaging Aggregation Operation
2. Transductive LSTM for time-series prediction: An application to weather forecasting
3. Time series classification with Echo Memory Networks
4. One-class graph neural networks for anomaly detection in attributed networks
5. Concept Drift Detection Delay Index
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