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dc.contributor.authorSmejkalova, Veronika
dc.contributor.authorSomplak, Radovan
dc.contributor.authorNevrly, Vlastimir
dc.contributor.authorPavlas, Martin
dc.date.accessioned2019-06-26T10:18:36Z
dc.date.available2019-06-26T10:18:36Z
dc.date.issued2018-06-01cs
dc.identifier.citationMendel. 2018 vol. 24, č. 1, s. 85-92. ISSN 1803-3814cs
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/179228
dc.description.abstractThe waste management is a dynamically progressive area, with the current trend leading to circular economy scheme. The development in this area requires quality prognosis reflecting the analysed timeframe. The forecast of the waste production and composition of waste is an important aspect with regards to the planning in waste management. However, the regular prognostic methods are not appropriate for these purposes due to short time series of historical data and unavailability of socio-economic data. The paper proposes a general approach via mathematical model for forecasting of future waste-related parameters based on spatially distributed data with hierarchical structure. The approach is based on principles of regression analysis with final balance to ensure the compliance of aggregated data values. The selection of the regression function is a part of mathematical model for high-quality description of data trend. In addition, outlier values are cleared, which occur abundantly in the database. The decomposition of the model into subtasks is performed in order to simpler implementation and reasonable time solvability. The individual algorithm steps are applied to municipal waste production data in the Czech Republic.en
dc.formattextcs
dc.format.extent85-92cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/27cs
dc.subjectwaste productionen
dc.subjectforecastingen
dc.subjectprognostic modelen
dc.subjectshort time seriesen
dc.subjectregression analysisen
dc.subjectnonlinear regressionen
dc.titleDesign and Decomposition of Waste Prognostic Model with Hierarchical Structuresen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
dc.coverage.issue1cs
dc.coverage.volume24cs
dc.identifier.doi10.13164/mendel.2018.1.085en
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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