Artificial intelligence-based approach for Univariate time-series Anomaly detection using Hybrid CNN-BiLSTM Model
Author:
Affiliation:
1. Military Technical College,Department of Astronautics Engineering,Alexandria,Egypt
2. Military Technical College,Department of Computer Engineering,Cairo,Egypt
3. Head Military Technical College,Astronautics Engineering Department,Cairo,Egypt
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9781836/9781818/09781894.pdf?arnumber=9781894
Reference11 articles.
1. Deep learning for anomaly detection: A survey;chalapathy,2019
2. Group Anomaly Detection: Past Notions, Present Insights, and Future Prospects
3. Cardiac Arrhythmia Detection from ECG Combining Convolutional and Long Short-Term Memory Networks
4. Multi-Objective Hybrid Artificial Intelligence Approach for Fault Diagnosis of Aerospace Systems
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