1 research outputs found
Comparing Multilayer Perceptron and Multiple Regression Models for Predicting Energy Use in the Balkans
Global demographic and economic changes have a critical impact on the total
energy consumption, which is why demographic and economic parameters have to be
taken into account when making predictions about the energy consumption. This
research is based on the application of a multiple linear regression model and
a neural network model, in particular multilayer perceptron, for predicting the
energy consumption. Data from five Balkan countries has been considered in the
analysis for the period 1995-2014. Gross domestic product, total number of
population, and CO2 emission were taken as predictor variables, while the
energy consumption was used as the dependent variable. The analyses showed that
CO2 emissions have the highest impact on the energy consumption, followed by
the gross domestic product, while the population number has the lowest impact.
The results from both analyses are then used for making predictions on the same
data, after which the obtained values were compared with the real values. It
was observed that the multilayer perceptron model predicts better the energy
consumption than the regression model.Comment: In proceedings of 4th Virtual International Conference on Science,
Technology and Management in Energy (eNergetics 2018