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The use of data mining methods for the psychoacoustic assessment of noise in urban environment

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

In studies on the assessment of the impact of environmental noise sources, depending on the objective set, there are used various supporting models and technologies. In the article, there was carried out the analysis of the selection of physical and psychoacoustic variables caused by the noise sources. They were determined the basic psychoacoustic measures of sound quality for registered acoustic signals in urban environment. The results were compared with the results obtained in the experiment. There was carried out the analysis of selection of input variables for the development of the model of the psychoacoustic assessment of noise, with the use of data mining methods, ie.: Principal Component Analysis and regression tree. The obtained results of the use of data maining methods were interpreted in the context of the results from the laboratory experiment done.

Original languageEnglish
Title of host publicationEducation and Accreditation in Geosciences; Environmental Legislation, Multilateral Relations And Funding Opportunities
PublisherInternational Multidisciplinary Scientific Geoconference
Pages1059-1066
Number of pages8
Edition52
ISBN (Print)9786197408263
DOIs
Publication statusPublished - 2017
Event17th International Multidisciplinary Scientific Geoconference, SGEM 2017 - Albena, Bulgaria
Duration: 29 Jun 20175 Jul 2017

Publication series

NameInternational Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
Number52
Volume17
ISSN (Print)1314-2704

Conference

Conference17th International Multidisciplinary Scientific Geoconference, SGEM 2017
Country/TerritoryBulgaria
CityAlbena
Period29/06/175/07/17

Keywords

  • Data mining
  • Psychoacoustic noise assessment
  • Urban environment

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Geology

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