Genetic Algorithm with Radial Basis Mapping Network for the Electricity Consumption Modeling
Israel Elias, José de Jesús Rubio, Dany Ivan Martinez, Tomas Miguel Vargas, V. Garcia, Dante Mújica‐Vargas, Jesús Alberto Meda-Campaña, Jaime Pacheco, G. Gutiérrez, Alejandro Zacarías
Abstract
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.