DETERMINING THE FACTORS THAT MOST AFFECT THE ECOLOGICAL FOOTPRINT UUSING THE ARTIFICIAL NEURAL NETWORK CLASSIFICATION FEATURE: THE CASE OF TURKEY

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dc.contributor.authorDemirbay, Sevim Gülin
dc.contributor.authorGündüz, Selim
dc.date.accessioned2025-01-06T17:23:04Z
dc.date.available2025-01-06T17:23:04Z
dc.date.issued2023
dc.departmentAdana Alparslan Türkeş Bilim ve Teknoloji Üniversitesi
dc.description.abstractSince the end of the 20th century, ecological problems have become a priority problem due to industrialization, urbanization, technological developments and rapid population growth. The change in human living standards causes many ecological problems such as unconscious consumption of natural resources, extinction of forests and living species. Ecological Footprint is developed to measure the demand pressure that people exert on the environment. In study, Neural Network Fitting Model was used in MATLAB, for the development Artificial Neural Network (ANN) by using the data of 1996-2018 to estimate Turkey's ecological footprint. Urban Population, Renewable Energy Consumption, R&D Expenditures and Human Development Index were chosen as independent variables. The data were obtained from the database of “World Bank Group” and “Human Development Reports”. For the ANN, Levenberg-Marquardt algorithm was used to determine the appropriate hidden layer and hidden neurons in each layer. The data used to train an artificial neural network using feedforward and backpropagation were randomly divided into three groups for training, testing and validation purposes. R values for each stage, respectively; 0.999, 0.948, was obtained as 1. According to the results obtained, the independent variable with the greatest effect on the ecological footprint was found to be the Urban Population.
dc.identifier.doi10.25287/ohuiibf.1206814
dc.identifier.endpage917
dc.identifier.issn2564-6931
dc.identifier.issue4
dc.identifier.startpage904
dc.identifier.trdizinid1207439
dc.identifier.urihttps://doi.org/10.25287/ohuiibf.1206814
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1207439
dc.identifier.urihttps://hdl.handle.net/20.500.14669/588
dc.identifier.volume16
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofÖmer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectArtificial Neural Networks
dc.subjectForecasting
dc.subjectEcological Footprint
dc.titleDETERMINING THE FACTORS THAT MOST AFFECT THE ECOLOGICAL FOOTPRINT UUSING THE ARTIFICIAL NEURAL NETWORK CLASSIFICATION FEATURE: THE CASE OF TURKEY
dc.typeArticle

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