Modeling and forecasting of the primary energy consumption (PEC) play a vital role for
policy makers and related organizations in developing countries such as Turkey. In this …

The main objective of the present study is to apply the artificial neural network (ANN)
methodology, linear regression (LR) and nonlinear regression (NLR) models to estimate the …

Forecasting of energy demand in emerging markets is one of the most important policy tools
used by the decision makers all over the world. In Turkey, most of the early studies used …

The need for energy supply, especially for electricity, has been increasing in the last two
decades in Turkey. In addition, owing to the uncertain economic structure of the country …

This study deals with the modeling of the energy consumption in Turkey in order to forecast
future projections based on socio-economic and demographic variables (gross domestic …

This paper proposes a new hybrid method (HAP) for estimating energy demand of Turkey
using Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). Proposed …

This study presents an integrated genetic algorithm (GA) and artificial neural network (ANN)
to estimate and predict electricity demand using stochastic procedures. The economic …

This study mathematically formulates the effects of socio-economic indicators (gross
domestic production, population, stock index, export, and import) on Iran's electric energy …

In this study forecast of Turkey's net electricity energy consumption on sectoral basis until
2020 is explored. Artificial neural networks (ANN) is preferred as forecasting tool. The …

This study presents an integrated algorithm for forecasting monthly electrical energy
consumption based on genetic algorithm (GA), computer simulation and design of …