Heuristic methodology for forecasting of quantities in waste management

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F17%3APU124850" target="_blank" >RIV/00216305:26210/17:PU124850 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.13164/mendel.2017.1.185" target="_blank" >http://dx.doi.org/10.13164/mendel.2017.1.185</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.13164/mendel.2017.1.185" target="_blank" >10.13164/mendel.2017.1.185</a>

Result language

angličtina

Original language name

Heuristic methodology for forecasting of quantities in waste management

Original language description

The forecast of waste production and disposal is an important requirement for a future waste management planning. The problem is very often a short time series of the database. This paper suggests an approach to forecast the production of multiple waste types in micro-regions taking into account this challenge by combining many techniques. The heuristic methodology consisting of few steps is formulated. First, the input data are transformed and the methods from cluster analysis are repetitively applied. The second step is about a determination of quality for trend functions based on historical data. In the last step is performed the testing. The different type of representatives from cluster analysis is used to calculate indices of determination which are compared. This procedure is repeated until the criteria hit. The proposed approach reduced the computational time and managed to aggregate micro-regions with a similar trend. The forecast should have contributions in terms of building new facilities or adaptations to the existing ones, where it is necessary to estimate the production of waste for several years in advance. The article includes a case study of production forecast for several waste types in territorial units of the Czech Republic. The forecast is based on data in years 2009--2014 and following year 2015 was used to assess the quality of the final models. In the future, the database will expand and thus it will be possible to make more precise estimates and to develop statistical methods to measure this prognostic tool.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10103 - Statistics and probability

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)

Publication year

2017

Confidentiality

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

Name of the periodical

Mendel Journal series

ISSN

1803-3814

e-ISSN

—

Volume of the periodical

2017

Issue of the periodical within the volume

1

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

8

Pages from-to

185-192

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85042253341