Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/13521
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dc.contributor.authorPetković, Biljana-
dc.contributor.authorAgdas A.-
dc.contributor.authorzandi, yousef-
dc.contributor.authorNikolic I.-
dc.contributor.authorDenic N.-
dc.contributor.authorRadenkovic, Sonja D.-
dc.contributor.authorAlmojil S.-
dc.contributor.authorRoco Videla A.-
dc.contributor.authorKojić N.-
dc.contributor.authorZlatkovic D.-
dc.contributor.authorStojanović, Biljana J.-
dc.date.accessioned2021-09-24T22:50:23Z-
dc.date.available2021-09-24T22:50:23Z-
dc.date.issued2021-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/13521-
dc.description.abstractIn a closed loop structure, the circular economy reflects a concept for converting material and energy wastes into capital for other purposes. The circular economy's key goal is to reduce energy and material waste. The best-case scenario will be to eliminate wastes and repurpose them, which is one of the key goals of the circular economy. One of the most important purposes of incorporating of circular economy are decreasing of environmental pollution and improving of sustainably development. The sustainably development could be represented by gross domestic product (GDP). The main goal of the study was to analyze the effect of waste generation, recycling, renewable energy, biomass and soil pollution on the GDP. For such a purpose adaptive neuro fuzzy inference system (ANFIS) was implemented since the methodology is suitable for statistical investigation of strongly nonlinear data sample due to features of fuzzy logic system. The combination of generated municipal waste, renewable energy supply and phosphorus balance per hectare represents the most influential combination for GDP prediction. The obtained results could represent the best practices for implementation of circular economy concept.-
dc.rightsrestrictedAccess-
dc.sourceRhizosphere-
dc.titleNeuro fuzzy evaluation of circular economy based on waste generation, recycling, renewable energy, biomass and soil pollution-
dc.typearticle-
dc.identifier.doi10.1016/j.rhisph.2021.100418-
dc.identifier.scopus2-s2.0-85111595939-
Appears in Collections:Faculty of Economics, Kragujevac

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