Non-intrusive Load Monitoring via Multi-label Sparse Representation based Classification
Signal Processing
2019-12-17 v1 Machine Learning
Systems and Control
Systems and Control
Machine Learning
Abstract
This work follows the approach of multi-label classification for non-intrusive load monitoring (NILM). We modify the popular sparse representation based classification (SRC) approach (developed for single label classification) to solve multi-label classification problems. Results on benchmark REDD and Pecan Street dataset shows significant improvement over state-of-the-art techniques with small volume of training data.
Cite
@article{arxiv.1912.07360,
title = {Non-intrusive Load Monitoring via Multi-label Sparse Representation based Classification},
author = {Shikha Singh and Angshul Majumdar},
journal= {arXiv preprint arXiv:1912.07360},
year = {2019}
}
Comments
The final version has been accepted at IEEE Transactions on Smartgrid