Heuristic Methodology for Forecasting of Production in Waste Management
| dc.contributor.author | Smejkalova, Veronika | |
| dc.contributor.author | Somplak, Radovan | |
| dc.contributor.author | Nevrly, Vlastimir | |
| dc.coverage.issue | 1 | cs |
| dc.coverage.volume | 23 | cs |
| dc.date.accessioned | 2019-06-26T10:18:10Z | |
| dc.date.available | 2019-06-26T10:18:10Z | |
| dc.date.issued | 2017-06-01 | cs |
| dc.description.abstract | 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 di erent 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 nal 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. | en |
| dc.format | text | cs |
| dc.format.extent | 185-192 | cs |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Mendel. 2017 vol. 23, č. 1, s. 185-192. ISSN 1803-3814 | cs |
| dc.identifier.doi | 10.13164/mendel.2017.1.185 | en |
| dc.identifier.issn | 2571-3701 | |
| dc.identifier.issn | 1803-3814 | |
| dc.identifier.uri | http://hdl.handle.net/11012/179216 | |
| dc.language.iso | en | cs |
| dc.publisher | Institute of Automation and Computer Science, Brno University of Technology | cs |
| dc.relation.ispartof | Mendel | cs |
| dc.relation.uri | https://mendel-journal.org/index.php/mendel/article/view/71 | cs |
| dc.rights.access | openAccess | en |
| dc.subject | forecasting | en |
| dc.subject | cluster analysis | en |
| dc.subject | waste production | en |
| dc.subject | short-time series | en |
| dc.subject | regression analysis | en |
| dc.title | Heuristic Methodology for Forecasting of Production in Waste Management | en |
| dc.type.driver | article | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| eprints.affiliatedInstitution.faculty | Fakulta strojního inženýrství | cs |
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