Unsupervised learning procedure for NILM applications
| Autor: | Gilles Jacobs, Pierre Henneaux |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry Nonintrusive load monitoring ComputerApplications_COMPUTERSINOTHERSYSTEMS Context (language use) Electric consumption 02 engineering and technology 010501 environmental sciences Machine learning computer.software_genre 01 natural sciences 0202 electrical engineering electronic engineering information engineering Unsupervised learning 020201 artificial intelligence & image processing Transient (computer programming) Artificial intelligence Cluster analysis business computer 0105 earth and related environmental sciences |
| Zdroj: | 2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON). |
| Popis: | In a domestic context, NILM applications (NonIntrusive Load Monitoring) allow users to know their electric consumption per appliance without having to install sensors for each appliance in their house. The aim of this paper is to present a new generic method allowing to discover the different appliances present in a house. Results obtained in this paper relies on supervised data obtained by sub-metering at the level of each appliance for 3 real domestic houses. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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