Estimates of energy consumption in Turkey using neural networks with the teaching–learning-based optimization algorithm

The main objective of the present study was to apply the ANN (artificial neural network) model with the TLBO (teaching–learning-based optimization) algorithm to estimate energy consumption in Turkey. Gross domestic product, population, import, and export data were selected as independent variables i...

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Vydané v:Energy (Oxford) Ročník 75; s. 295 - 303
Hlavní autori: Uzlu, Ergun, Kankal, Murat, Akpınar, Adem, Dede, Tayfun
Médium: Journal Article Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: Kidlington Elsevier Ltd 01.10.2014
Elsevier
Predmet:
Algorithms
Applied sciences
data collection
Energy
Energy consumption
Energy consumption/demand
Estimates
Exact sciences and technology
exports
gross domestic product
imports
Learning theory
Mathematical models
natural resources
Neural networks
oils
Optimization
Projection
Teaching–learning-based optimization algorithm
Turkey
Turkey (country)
Asia
Turkey
Turkey (country)
Teaching–learning-based optimization algorithm
Turkey
Energy consumption/demand
Neural networks
Energy consumption
Neural network
Algorithm
Optimization
Teaching
ISSN:0360-5442
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Shrnutí:The main objective of the present study was to apply the ANN (artificial neural network) model with the TLBO (teaching–learning-based optimization) algorithm to estimate energy consumption in Turkey. Gross domestic product, population, import, and export data were selected as independent variables in the model. Performances of the ANN–TLBO model and the classical back propagation-trained ANN model (ANN–BP (teaching–learning-based optimization) model) were compared by using various error criteria to evaluate the model accuracy. Errors of the training and testing datasets showed that the ANN–TLBO model better predicted the energy consumption compared to the ANN–BP model. After determining the best configuration for the ANN–TLBO model, the energy consumption values for Turkey were predicted under three scenarios. The forecasted results were compared between scenarios and with projections by the MENR (Ministry of Energy and Natural Resources). Compared to the MENR projections, all of the analyzed scenarios gave lower estimates of energy consumption and predicted that Turkey's energy consumption would vary between 142.7 and 158.0 Mtoe (million tons of oil equivalent) in 2020. •This study is associated with predicting energy consumption in Turkey.•GDP (gross domestic product), population, import and export were used as predictor variables.•TLBO (teaching–learning-based optimization) and BP (back-propagation) were used to train ANNs (artificial neural networks).•ANN–TLBO predicted the energy consumption more accurately than ANN–BP.•Using the ANN–TLBO model, the energy consumption was forecasted until 2020.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0360-5442
DOI:10.1016/j.energy.2014.07.078