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 (Applied Sciences, 2020)
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.