Prediction of net energy consumption based on economic indicators (GNP and GDP) in Turkey

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dc.contributor.authorSözen, Adnan
dc.contributor.authorArcaklıoğlu, Erol
dc.date.accessioned2020-06-25T17:43:37Z
dc.date.available2020-06-25T17:43:37Z
dc.date.issued2007
dc.descriptionARCAKLIOGLU, Erol/0000-0001-8073-5207;
dc.description.abstractThe most important theme in this study is to obtain equations based on economic indicators (gross national product - GNP and gross domestic product - GDP) and population increase to predict the net energy consumption of Turkey using artificial neural networks (ANNs) in order to determine future level of the energy consumption and make correct investments in Turkey. In this study, three different models were used in order to train the ANN. In one of them (Model 1), energy indicators such as installed capacity, generation, energy import and energy export, in second (Model 2), GNP was used and in the third (Model 3), GDP was used as the input layer of the network. The net energy consumption (NEC) is in the output layer for all models. In order to train the neural network, economic and energy data for last 37 years (1968-2005) are used in network for all models. The aim of used different models is to demonstrate the effect of economic indicators on the estimation of NEC. The maximum mean absolute percentage error (MAPE) was found to be 2.322732, 1.110525 and 1.122048 for Models 1, 2 and 3, respectively. R 2 values were obtained as 0.999444, 0.999903 and 0.999903 for training data of Models 1, 2 and 3, respectively. The ANN approach shows greater accuracy for evaluating NEC based on economic indicators. Based on the outputs of the study, the ANN model can be used to estimate the NEC from the country's population and economic indicators with high confidence for planing future projections. (D 2007 Elsevier Ltd. All rights reserved.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1016/j.enpol.2007.04.029
dc.identifier.endpage4992en_US
dc.identifier.issn0301-4215
dc.identifier.issn1873-6777
dc.identifier.issue10en_US
dc.identifier.scopus2-s2.0-34447526121
dc.identifier.scopusqualityQ1
dc.identifier.startpage4981en_US
dc.identifier.urihttps://doi.org10.1016/j.enpol.2007.04.029
dc.identifier.urihttps://hdl.handle.net/20.500.12587/3828
dc.identifier.volume35en_US
dc.identifier.wosWOS:000250320800019
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofEnergy Policy
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectenergy consumptionen_US
dc.subjecteconomic indicatoren_US
dc.subjectartificial neural networken_US
dc.titlePrediction of net energy consumption based on economic indicators (GNP and GDP) in Turkeyen_US
dc.typeArticle

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