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dc.creatorAdamović, Vladimir M.
dc.creatorAntanasijević, Davor
dc.creatorRistić, Mirjana
dc.creatorPerić-Grujić, Aleksandra
dc.creatorPocajt, Viktor
dc.date.accessioned2021-03-10T13:50:25Z
dc.date.available2021-03-10T13:50:25Z
dc.date.issued2018
dc.identifier.issn1438-4957
dc.identifier.urihttp://TechnoRep.tmf.bg.ac.rs/handle/123456789/3994
dc.description.abstractThis paper presents a development of general regression neural network (a form of artificial neural network) models for the prediction of annual quantities of hazardous chemical and healthcare waste at the national level. Hazardous waste is being generated from many different sources and therefore it is not possible to conduct accurate predictions of the total amount of hazardous waste using traditional methodologies. Since they represent about 40% of the total hazardous waste in the European Union, chemical and healthcare waste were specifically selected for this research. Broadly available social, economic, industrial and sustainability indicators were used as input variables and the optimal sets were selected using correlation analysis and sensitivity analysis. The obtained values of coefficients of determination for the final models were 0.999 for the prediction of chemical hazardous waste and 0.975 for the prediction of healthcare and biological hazardous waste. The predicting capabilities of the models for both types of waste are high, since there were no predictions with errors greater than 25%. Also, results of this research demonstrate that the human development index can replace gross domestic product and in this context even represent a better indicator of socio-economic conditions at the national level.en
dc.publisherSpringer, New York
dc.relationinfo:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/172007/RS//
dc.rightsrestrictedAccess
dc.sourceJournal of Material Cycles and Waste Management
dc.subjectHazardous wasteen
dc.subjectChemical wasteen
dc.subjectHealthcare wasteen
dc.subjectMedical wasteen
dc.subjectArtificial neural networksen
dc.titleAn optimized artificial neural network model for the prediction of rate of hazardous chemical and healthcare waste generation at the national levelen
dc.typearticle
dc.rights.licenseARR
dc.citation.epage1750
dc.citation.issue3
dc.citation.other20(3): 1736-1750
dc.citation.rankM22
dc.citation.spage1736
dc.citation.volume20
dc.identifier.doi10.1007/s10163-018-0741-6
dc.identifier.scopus2-s2.0-85048873652
dc.identifier.wos000435811400033
dc.type.versionpublishedVersion


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