Article ID: | iaor20116384 |
Volume: | 39 |
Issue: | 8 |
Start Page Number: | 4644 |
End Page Number: | 4650 |
Publication Date: | Aug 2011 |
Journal: | Energy Policy |
Authors: | Geem Zong Woo |
Keywords: | energy, neural networks, simulation, forecasting: applications, economics, statistics: regression |
Artificial neural network models were developed to forecast South Korea's transport energy demand. Various independent variables, such as GDP, population, oil price, number of vehicle registrations, and passenger transport amount, were considered and several good models (Model 1 with GDP, population, and passenger transport amount; Model 2 with GDP, number of vehicle registrations, and passenger transport amount; and Model 3 with oil price, number of vehicle registrations, and passenger transport amount) were selected by comparing with multiple linear regression models. Although certain regression models obtained better