Load Identification System for Residential Applications Based on the NILM Technique
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9123988/9128363/09128599.pdf?arnumber=9128599
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A Non-Intrusive Load Disaggregation Tool based on Smart Meter Data for Residential Buildings;2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe);2023-06-06
2. A New NILM System Based on the SFRA Technique and Machine Learning;Sensors;2023-05-31
3. Event-driven non-intrusive load monitoring algorithm based on targeted mining multidimensional load characteristics;China Communications;2023-05
4. An Embedded Deep Learning NILM System: A Year-Long Field Study in Real Houses;IEEE Transactions on Instrumentation and Measurement;2023
5. A Review of Non-Intrusive Load Monitoring Applications in Industrial and Residential Contexts;Energies;2022-11-28
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