Sample Efficient Home Power Anomaly Detection in Real Time Using Semi-Supervised Learning

Sample Efficient Home Power Anomaly Detection in Real Time Using Semi-Supervised Learning

Anomaly detection in home power monitoring can be categorized into two main types: detection of electrical theft, leakage, or nontechnical loss and monitoring anomalies in the daily activities of residents. Focusing on the application and practicality of anomaly detection, we propose sample efficien...

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Bibliographic Details
Main Authors: Xinlin Wang, Insoon Yang, Sung-Hoon Ahn
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Anomaly detection
power monitoring
support vector machine
semi-supervised learning
Online Access:https://ieeexplore.ieee.org/document/8848388/

Internet

https://ieeexplore.ieee.org/document/8848388/

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