Anomaly Detection in Power Generation Plants with Generative Adversarial Networks
Author:
Affiliation:
1. Department of Mathematics, Rhodes University,Grahamstown 6139,South Africa
2. Department of Computer Science and Information Systems University of Limerick,Limerick Ireland,AIMS Kigali,Rwanda
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10389177/10389181/10389251.pdf?arnumber=10389251
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3. Power Consumption: Base Stations of Telecommunication in Sahel Zone of Cameroon: Typology Based on the Power Consumption—Model and Energy Savings
4. On the nature and types of anomalies: a review of deviations in data
5. Deep learning for anomaly detection: A review;Pang,2021
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