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dc.contributor.authorJanković, Radmilaen_US
dc.contributor.authorMihajlović, Ivanen_US
dc.contributor.authorAmelio, Alessiaen_US
dc.contributor.authorDraganov, Ivo R.en_US
dc.date.accessioned2021-08-24T10:14:57Z-
dc.date.available2021-08-24T10:14:57Z-
dc.date.issued2021-07-28-
dc.identifier.isbn9781665428873-
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/4647-
dc.description.abstractThis paper introduces a new prediction model of the ecological footprint from energy parameters based on time series vector autoregression. The experiment employs global yearly observations of the variables in the period 1971-2014 for three countries: (i) Italy, (ii) Pakistan, and (iii) China. A prediction is performed for each variable adopted in the model from 2015 to 2024. The obtained results indicate that the total ecological footprint of consumption will increase for China and Pakistan, and decrease for Italy.en_US
dc.publisherIEEEen_US
dc.subjectEcological footprint | Energy | Prediction model | Time series analysisen_US
dc.titlePredicting the Ecological Footprint: A Case Study for Italy, Pakistan and Chinaen_US
dc.typeConference Paperen_US
dc.relation.conference56th International Scientific Conference on Information, Communication and Energy Systems and Technologies, ICEST 2021, Sozopol, 16 June 2021 - 18 June 2021en_US
dc.identifier.doi10.1109/ICEST52640.2021.9483528-
dc.identifier.scopus2-s2.0-85112253212-
dc.contributor.affiliationComputer Scienceen_US
dc.contributor.affiliationMathematical Institute of the Serbian Academy of Sciences and Arts-
dc.relation.firstpage9483528-
dc.description.rankM33-
item.cerifentitytypePublications-
item.openairetypeConference Paper-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.orcid0000-0003-3424-134X-
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