Publication detail

Heuristic Approach to Multivariate Inverse Prediction Problem Using Data Reconciliation

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

Original Title

Heuristic Approach to Multivariate Inverse Prediction Problem Using Data Reconciliation

Type

journal article in Scopus

Language

English

Original Abstract

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.

Keywords

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

Authors

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

Released

26. 6. 2018

Publisher

VUT

Location

Brno

ISBN

1803-3814

Periodical

Mendel Journal series

Year of study

2018

Number

1

State

Czech Republic

Pages from

71

Pages to

78

Pages count

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"
}