Non-intrusive Load Monitoring for Household Energy Disaggregation: A State-of-the-Art
Author:
Affiliation:
1. University of Electronic Science and Technology of China (UESTC),School of Mechanical and Electrical Engineering,Chengdu,China,611731
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10115460/10115466/10116809.pdf?arnumber=10116809
Reference68 articles.
1. Deep Recurrent Neural Network to Disaggregate Household Energy Consumption;linh,2017
2. Electrical-end-use data from 23 houses sampled each minute for simulating micro-generation systems
3. Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey
4. Energy Smart Home Lab (ESHL);kochanneck,2016
5. Multi-Label Learning for Appliance Recognition in NILM Using Fryze-Current Decomposition and Convolutional Neural Network
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