Regression Models Comparison for Efficiency in Electricity Consumption in Ecuadorian Schools: A Case of Study

  • Alejandro Toapanta-LemaEmail author
  • Walberto Gallegos
  • Jefferson Rubio-Aguilar
  • Edilberto Llanes-Cedeño
  • Jorge Carrascal-García
  • Letty García-López
  • Paul D. Rosero-Montalvo
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1194)


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.


Regression models Electric consume prediction 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Alejandro Toapanta-Lema
    • 1
    • 2
    Email author
  • Walberto Gallegos
    • 1
  • Jefferson Rubio-Aguilar
    • 1
  • Edilberto Llanes-Cedeño
    • 1
  • Jorge Carrascal-García
    • 2
  • Letty García-López
    • 2
  • Paul D. Rosero-Montalvo
    • 3
  1. 1.Universidad Internacional SEKQuitoEcuador
  2. 2.Instituto Superior TecnológicoUrcuquíEcuador
  3. 3.Universidad Técnica del NorteIbarraEcuador

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