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Design and Decomposition of Waste Prognostic Model with Hierarchical Structures

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27-Article Text-70-1-10-20190218.pdf (692.0KB)
Data
2018-06-01
Autor
Smejkalova, Veronika
Somplak, Radovan
Nevrly, Vlastimir
Pavlas, Martin
Altmetrics
10.13164/mendel.2018.1.085
Metadata
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Streszczenie
The 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.
Keywords
waste production, forecasting, prognostic model, short time series, regression analysis, nonlinear regression
URI
http://hdl.handle.net/11012/179228
Document type
Peer reviewed
Document version
Final PDF
Source
Mendel. 2018 vol. 24, č. 1, s. 85-92. ISSN 1803-3814
https://mendel-journal.org/index.php/mendel/article/view/27
DOI
10.13164/mendel.2018.1.085
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  • Vol. 24, No. 1 [24]
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