Please use this identifier to cite or link to this item: http://repositorio.uisek.edu.ec/handle/123456789/3990
Title: Regression Models Comparison for Efficiency in Electricity Consumption in Ecuadorian Schools: A Case of Study
Authors: Rubio-Aguilar, Jefferson
Toapanta-Lema, Alejandro
Gallegos, Walberto
Llanes-Cedeño, Edilberto
Carrascal-García, Jorge
García-López, Letty
Rosero-Montalvo, Paul D.
Keywords: REGRESSION MODELS
ELECTRIC CONSUME PREDICTION
Issue Date: 3-Mar-2020
Publisher: SpringerLink
Citation: PUB R896r/2020
Abstract: Consumption forecast models with their proper billing allow establishing strategies to avoid overloads in systems and penalties for high consumption. This paper presents a comparison of multivariate data prediction models that allow detecting the final monthly cost of electricity consumption in relation to the different billing parameters. As relevant results, it was obtained that the models based on decision support machines have a better sensitivity when compared with different metrics that evaluate the prediction error with training set improved by backward elimination criteria.
URI: http://repositorio.uisek.edu.ec/handle/123456789/3990
ISBN: 978-3-030-42519-7
Appears in Collections:Publicaciones UISEK

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