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A data-driven forecasting strategy to predict 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., Luis Gonzalez-Morales, Luiz G. González, Mariano-Hernández D., Santos-García F., Solís M., Zorita-Lamadrid Á.L.Fuentes:scopusAnalysis 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., Luis Gonzalez-Morales, Luiz G. González, Mariano-Hernández D., Ospino-Castro A., Santos-García F., Solís M., Zorita-Lamadrid Á.L.Fuentes:scopusComparative study of continuous hourly energy consumption forecasting strategies with small data sets to support demand management decisions in buildings
ArticleAbstract: Buildings are one of the largest consumers of electrical energy, making it important to develop diffPalabras claves:building energy consumption, forecasting, learning algorithms, multistep forecasting, Short-term forecastingAutores:Alonso-Gómez V., Duque-Pérez O., Hernandez-Callejo L., Jaramillo-Duque A., Luis Gonzalez-Morales, Luiz G. González, Mariano-Hernández D., Santos-García F., Solís M., Zorita-Lamadrid Á.L.Fuentes:scopus