Non-Intrusive Load Monitoring via Multi-Label Sparse Representation-Based Classification

被引：36

作者：

Singh, Shikha ^{[1
]}

Majumdar, Angshul ^{[1
]}

机构：

[1] Indraprastha Inst Informat Technol Delhi, Dept Elect & Commun Engn, New Delhi 110020, India

来源：

IEEE TRANSACTIONS ON SMART GRID | 2020年 / 11卷 / 02期

关键词：

NILM; energy disaggregation; multi-label classification;

D O I：

10.1109/TSG.2019.2938090

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：1799 / 1801

页数：3

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