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ŠOMPLÁK, R. ZAVÍRALOVÁ, L. PAVLAS, M. NEVRLÝ, V. POPELA, P.
Original Title
Input data validation for complex supply chain models applied to waste management
Type
journal article in Scopus
Language
English
Original Abstract
This contribution focuses on comprehensive input data analysis prior to the application of complex network flow models. Network flow models are composed of vertices interconnected by edges, the number of which is dependent on particular problem studied. Any quantitative data in vertices may contain inaccurate information. The article is intent on computational system for simulation and forecasting in waste management incomplete data problems. The article introduces enhancements to the mathematical model of previously published tool and its elements. The focus is put on the suitable choice of weights for all input forecasting models and territorial divisions of relevant regions. Another model improvement is based on the support of adding new constraints that link multiple types of waste. The next part of article concentrates on forecasting of waste production by the application of the advanced model. The case study focused on the estimation of trends in data for municipal waste and composition of residual municipal solid waste in the Czech Republic is presented as well.
Keywords
Forecasting, Trend Analysis, Residual solid waste, Data validation, Justine
Authors
ŠOMPLÁK, R.; ZAVÍRALOVÁ, L.; PAVLAS, M.; NEVRLÝ, V.; POPELA, P.
Released
20. 3. 2017
ISBN
978-88-95608-47-1
Book
Chemical engineering transactions
2283-9216
Periodical
Chemical Engineering Transactions
Year of study
56
Number
1
State
Republic of Italy
Pages from
1921
Pages to
1926
Pages count
6
BibTex
@article{BUT131344, author="Radovan {Šomplák} and Lenka {Szásziová} and Martin {Pavlas} and Vlastimír {Nevrlý} and Pavel {Popela}", title="Input data validation for complex supply chain models applied to waste management", journal="Chemical Engineering Transactions", year="2017", volume="56", number="1", pages="1921--1926", doi="10.3303/CET1756321", issn="2283-9216" }