Applied Sciences (Jun 2020)

Genetic Algorithm with Radial Basis Mapping Network for the Electricity Consumption Modeling

  • Israel Elias,
  • José de Jesús Rubio,
  • Dany Ivan Martinez,
  • Tomas Miguel Vargas,
  • Victor Garcia,
  • Dante Mujica-Vargas,
  • Jesus Alberto Meda-Campaña,
  • Jaime Pacheco,
  • Guadalupe Juliana Gutierrez,
  • Alejandro Zacarias

DOI
https://doi.org/10.3390/app10124239
Journal volume & issue
Vol. 10, no. 12
p. 4239

Abstract

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The modified backpropagation algorithm based on the backpropagation with momentum is used for the parameters updating of a radial basis mapping (RBM) network, where it requires of the best hyper-parameters for more precise modeling. Seeking of the best hyper-parameters in a model it is not an easy task. In this article, a genetic algorithm is used to seek of the best hyper-parameters in the modified backpropagation for the parameters updating of a RBM network, and this RBM network is used for more precise electricity consumption modeling in a city. The suggested approach is called genetic algorithm with a RBM network. Additionally, since the genetic algorithm with a RBM network starts from the modified backpropagation, we compare both approaches for the electricity consumption modeling in a city.

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