Temporal Patternization of Power Signatures for Appliance Classification in NILM
Non-Intrusive Load Monitoring (NILM) techniques are effective for managing energy and for addressing imbalances between the energy demand and supply. Various studies based on deep learning have reported the classification of appliances from aggregated power signals. In this paper, we propose a novel...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-05-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/14/10/2931 |