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Analysis of the Integration of Drift Detection Methods in Learning Algorithms for Electrical Consumption Forecasting in Smart Buildings
ArticleAbstract: Buildings are currently among the largest consumers of electrical energy with considerable increasesPalabras claves:drift detection, electrical consumption forecasting, energy forecasting, Machine learning, Smart BuildingsAutores:Alonso-Gómez V., Bello H.J., Duque-Pérez O., García F.S., Hernandez-Callejo L., Jaramillo-Duque A., Luiz G. González, Mariano-Hernández D., Ospino-Castro A., Solís M., Zorita-Lamadrid Á.L.Fuentes:scopusA data-driven forecasting strategy to pbkp_redict continuous hourly energy demand in smart buildings
ArticleAbstract: Smart buildings seek to have a balance between energy consumption and occupant com-fort. To make thiPalabras claves:Energy consumption, forecasting models, Multi-step forecasting, Short-term forecasting, smart buildingAutores:Duque-Pérez O., Hernandez-Callejo L., Luiz G. González, Mariano-Hernández D., Santos-García F., Solís M., Zorita-Lamadrid Á.L.Fuentes:scopus