An End-to-End Machine Learning based Unified Architecture for Non-Intrusive Load Monitoring

An End-to-End Machine Learning based Unified Architecture for Non-Intrusive Load Monitoring

Non-Intrusive Load Monitoring (NILM) or load disaggregation aims to analyze power consumption by decomposing the energy measured at the aggregate level into constituent appliances level. The conventional load disaggregation framework consists of signal processing and machine learning-based pipelined...

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Bibliographic Details
Main Authors: S. Wali, M. H. U. Haq, M. Kazmi, S. A. Qazi
Format: Article
Language:English
Published: D. G. Pylarinos 2021-06-01
Series:Engineering, Technology & Applied Science Research
Subjects:
non-intrusive load monitoring
gated recurrent units
end-to-end machine learning
reference energy disaggregation dataset
Online Access:https://www.etasr.com/index.php/ETASR/article/view/4142

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https://www.etasr.com/index.php/ETASR/article/view/4142

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