Analysis of the integration of drift detection methods in learning algorithms for electrical consumption forecasting in smart buildings

Autor: Víctor Alonso Gómez, Adalberto Ospino C., Felix Santos Garcia, Luis Hernández Callejo, Hugo J. Bello, Oscar Duque-Perez, Álvaro Jaramillo Duque, Martín Solís, Luis Gerardo Gonzalez Morales, Deyslen Mariano, Angel Luis Zorita Lamadrid

Publikováno v: REDICUC-Repositorio CUC
Corporación Universidad de la Costa
instacron:Corporación Universidad de la Costa
Sustainability; Volume 14; Issue 10; Pages: 5857

Buildings are currently among the largest consumers of electrical energy with considerable increases in CO2 emissions in recent years. Although there have been notable advances in energy efficiency, buildings still have great untapped savings potenti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78e4669f4b9860077dab77324712e9a6
https://repositorio.cuc.edu.co/

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