Please use this identifier to cite or link to this item: http://repositorio.uisek.edu.ec/handle/123456789/4201
Title: Prediction of monthly electricity consumption by cantons in Ecuador through neural networks: a case study
Authors: Llanes Cedeño, Edilberto Antonio
Guachimboza Davalos, Jorge I.
Rubio Aguiar, Rodolfo J.
Peralta Zurita, Diana Belén
Núñez Barrionuevo, Oscar F.
Keywords: POWER CONSUMPTION
MULTIVARIATE REGRESSION
NEURAL NET
WORK
Issue Date: 11-Nov-2020
Publisher: Springer, Cham
Abstract: Abstract. The present work shows a multivariate regression through deep learning related to energy consumption in the province of Pichincha- Ecuador in relation to its cantons. This is done to establish consumption habits in relation to the existing population. For this, a data preprocess- ing stage was implemented and later an artificial neural network of a hidden layer and 15 neurons. As a result, a mathematical model with an absolute error of 2.2 % is obtained.
URI: https://repositorio.uisek.edu.ec/handle/123456789/4201
ISBN: 978-3-030-59193-9
978-3-030-59194-6
Appears in Collections:Publicaciones UISEK

Files in This Item:
File Description SizeFormat 
978-3-030-59193-9 LLANES EDILBERTO 2020-11-11.pdf344.54 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.