<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The paper presents results of multivariate analysis of variations of radon concentrations in the shallow underground laboratory and a family house, depending on meteorological variables only. All available multivariate classification and regression methods, developed for data analysis in high-energy physics and implemented in the toolkit for multivariate analysis (TMVA) software package in ROOT, are used in the analysis. The result of multivariate regression analysis is a mapped functional behaviour of variations of radon concentration depending on meteorological variables only, which can be used for the evaluation of radon concentration, as well as to help with modelling of variation of radon concentration. The results of analysis of the radon concentration variations in the underground laboratory and real indoor environment, using multivariate methods, demonstrated the potential usefulness of these methods. Multivariate analysis showed that there is a potentially considerable prediction power of variations of indoor radon concentrations based on the knowledge of meteorological variables only. In addition, the online system using the resulting mapped functional behaviour for underground laboratory in the Institute of Physics Belgrade is implemented, and the resulting evaluation of radon concentrations are presented in this paper.</p></abstract>

The paper presents results of multivariate analysis of variations of radon concentrations in the shallow underground laboratory and a family house, depending on meteorological variables only. All available multivariate classification and regression methods, developed for data analysis in high-energy physics and implemented in the toolkit for multivariate analysis (TMVA) software package in ROOT, are used in the analysis. The result of multivariate regression analysis is a mapped functional behaviour of variations of radon concentration depending on meteorological variables only, which can be used for the evaluation of radon concentration, as well as to help with modelling of variation of radon concentration. The results of analysis of the radon concentration variations in the underground laboratory and real indoor environment, using multivariate methods, demonstrated the potential usefulness of these methods. Multivariate analysis showed that there is a potentially considerable prediction power of variations of indoor radon concentrations based on the knowledge of meteorological variables only. In addition, the online system using the resulting mapped functional behaviour for underground laboratory in the Institute of Physics Belgrade is implemented, and the resulting evaluation of radon concentrations are presented in this paper.

The use of multivariate analysis of the radon variability in the underground laboratory and indoor environment

Institute of Physics Belgrade, University of Belgrade, 118 Pregrevica Str., 11080 Belgrade,

Nukleonika

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The paper presents results of multivariate analysis of variations of radon concentrations in the shallow underground laboratory and a family house, depending...

The use of multivariate analysis of the radon variability in the underground laboratory and indoor environment

Publié en ligne: 10 sept. 2016

Pages: 357 - 360

Reçu: 04 janv. 2016

Accepté: 24 mars 2016

DOI: https://doi.org/10.1515/nuka-2016-0059

Mots clés
multivariate analysis, radon variability

© 2016 Jelena Filipović et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The use of multivariate analysis of the radon variability in the underground laboratory and indoor environment

Publié en ligne: 10 sept. 2016

Pages: 357 - 360

Reçu: 04 janv. 2016

Accepté: 24 mars 2016

DOI: https://doi.org/10.1515/nuka-2016-0059

Mots clésmultivariate analysis, radon variability

© 2016 Jelena Filipović et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
multivariate analysis, radon variability