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Design and Decomposition of Waste Prognostic Model with Hierarchical Structures

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F18%3APU129017" target="_blank" >RIV/00216305:26210/18:PU129017 - isvavai.cz</a>

  • Result on the web

    <a href="https://mendel-journal.org/index.php/mendel/article/view/27" target="_blank" >https://mendel-journal.org/index.php/mendel/article/view/27</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.13164/mendel.2018.1.085" target="_blank" >10.13164/mendel.2018.1.085</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Design and Decomposition of Waste Prognostic Model with Hierarchical Structures

  • Original language description

    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 hisorical 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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

    <a href="/en/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Sustainable Process Integration Laboratory (SPIL)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Mendel Journal series

  • ISSN

    1803-3814

  • e-ISSN

  • Volume of the periodical

    2018

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    8

  • Pages from-to

    85-92

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85071994232