A Parallel Evolutionary Computing-Embodied Artificial Neural Network Applied to Non-Intrusive Load Monitoring for Demand-Side Management in a Smart Home: Towards Deep Learning

Non-intrusive load monitoring (NILM) is a cost-effective approach that electrical appliances are identified from aggregated whole-field electrical signals, according to their extracted electrical characteristics, with no need to intrusively deploy smart power meters (power plugs) installed for indiv...

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Detalles Bibliográficos
Autor principal: Lin, Yu-Hsiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146608/
https://www.ncbi.nlm.nih.gov/pubmed/32188065
http://dx.doi.org/10.3390/s20061649

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146608/
https://www.ncbi.nlm.nih.gov/pubmed/32188065
http://dx.doi.org/10.3390/s20061649

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