Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/11324
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dc.rights.licenserestrictedAccess-
dc.contributor.authorStevanovic, Mirjana-
dc.contributor.authorVujicic, Sladjana-
dc.contributor.authorGajic A.-
dc.date.accessioned2021-04-20T18:03:58Z-
dc.date.available2021-04-20T18:03:58Z-
dc.date.issued2018-
dc.identifier.issn0378-4371-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/11324-
dc.description.abstract© 2017 Elsevier B.V. The main goal of the paper was to estimate gross domestic product (GDP) based on electricity estimation by artificial neural network (ANN). The electricity utilization was analyzed based on different sources like renewable, coal and nuclear sources. The ANN network was trained with two training algorithms namely extreme learning method and back-propagation algorithm in order to produce the best prediction results of the GDP. According to the results it can be concluded that the ANN model with extreme learning method could produce the acceptable prediction of the GDP based on the electricity utilization.-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.sourcePhysica A: Statistical Mechanics and its Applications-
dc.titleGross domestic product estimation based on electricity utilization by artificial neural network-
dc.typearticle-
dc.identifier.doi10.1016/j.physa.2017.07.023-
dc.identifier.scopus2-s2.0-85026727387-
Appears in Collections:Faculty of Engineering, Kragujevac

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