Detail publikace

Heuristic Approach to Multivariate Inverse Prediction Problem Using Data Reconciliation

ROSECKÝ, M. ŠOMPLÁK, R. JANOŠŤÁK, F. BEDNÁŘ, J.

Originální název

Heuristic Approach to Multivariate Inverse Prediction Problem Using Data Reconciliation

Typ

článek v časopise ve Scopus, Jsc

Jazyk

angličtina

Originální abstrakt

Some engineering waste management tasks require a complete data sets of its production. However, these sets are not available in most cases. Whether they are not archiving at all or are unavailable for their sensitivity. This article deals with the issue of incomplete datasets at the microregional level. For estimates, the data from higher territorial units and additional information from the micro-region are used. The techniques used in this estimation are illustrated by an example in the field of waste management. In particular, it is an estimate of the amount of waste in individual municipalities. It is based on recorded waste production at district level and total waste management costs, which is available at a municipal level. To estimate the waste production, combinations of linear regression models with random forest models were used, followed by correction by quadratic and nonlinear optimization models. Such task could be seen as a multivariate version of inverse prediction (or calibraion) problem, which is not solvable analytically. To test this approach, data for 2010 - 2015 measured in the Czech Republic were used.

Klíčová slova

Data reconciliation; Random forest; Regression; Waste management; Optimization; Multivariate calibration; Inverse prediction

Autoři

ROSECKÝ, M.; ŠOMPLÁK, R.; JANOŠŤÁK, F.; BEDNÁŘ, J.

Vydáno

26. 6. 2018

Nakladatel

VUT

Místo

Brno

ISSN

1803-3814

Periodikum

Mendel Journal series

Ročník

2018

Číslo

1

Stát

Česká republika

Strany od

71

Strany do

78

Strany počet

8

URL

https://mendel-journal.org/index.php/mendel/article/view/25

BibTex

@article{BUT149953,
  author="Martin {Rosecký} and Radovan {Šomplák} and František {Janošťák} and Josef {Bednář}",
  title="Heuristic Approach to Multivariate Inverse Prediction Problem Using Data Reconciliation",
  journal="Mendel Journal series",
  year="2018",
  volume="2018",
  number="1",
  pages="71--78",
  doi="10.13164/mendel.2018.1.071",
  issn="1803-3814",
  url="https://mendel-journal.org/index.php/mendel/article/view/25"
}