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Application of classification trees to identify embankment seepage

cris.lastimport.scopus2024-09-18T01:31:33Z
dc.abstract.enThe article discusses a method to control seepage in shafts. A special shaft model was built for this purpose. The paper mainly focuses on electrical impedance tomography with image reconstruction where the machine learning method was used, then the reconstruction results were compared and different numerical models were applied. The key parameters in electrical tomography are the speed of analysis and the accuracy of the reconstructed objects. Applications most often present challenges in obtaining spatial data from observations outside the measurement limits. Inverse problems are solved to obtain the reconstruction algorithm. The main advantage of the discussed solution is the possibility of analysing multidimensional data as well as high processing speed. Classification trees were used to obtain feedback on the degree of embankment seepage.
dc.affiliationTransportu i Informatyki
dc.contributor.authorKrzysztof Król
dc.contributor.authorTomasz Rymarczyk
dc.contributor.authorKonrad Niderla
dc.contributor.authorMichał Oleszek
dc.contributor.authorP Bożek
dc.contributor.authorP Tchórzewski
dc.contributor.authorE Kozłowski
dc.date.accessioned2024-08-06T12:05:54Z
dc.date.available2024-08-06T12:05:54Z
dc.date.issued2022
dc.identifier.doi10.1088/1742-6596/2408/1/012022
dc.identifier.eissn1742-6596
dc.identifier.issn1742-6588
dc.identifier.urihttps://repo.akademiawsei.eu/handle/item/569
dc.pbn.affiliationinformation and communication technology
dc.relation.ispartofJournal of Physics: Conference Series
dc.rightsCC-BY
dc.subject.enclassification trees
dc.subject.enidentification of embankment seepage
dc.subject.enseepage
dc.subject.enembankment seepage
dc.titleApplication of classification trees to identify embankment seepage
dc.typeReviewArticleConference
dspace.entity.typePublication
oaire.citation.issue1
oaire.citation.volume2408