Application of classification trees to identify embankment seepage
Ładowanie...
Data
2022
Inny tytuł
Typ
Artykuł recenzyjny (pokonferencyjny)
Redaktor
dc.contributor.advisor
Dyscyplina PBN
Informatyka techniczna i telekomunikacja
Czasopismo lub seria
Journal of Physics: Conference Series
ISSN
1742-6588
ISBN
DOI
10.1088/1742-6596/2408/1/012022
Strona internetowa
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Wydawca
Wydanie
Numer
Strony od-do
Tytuł monografii
item.page.defence
Tytuł tomu
Opis
Rodzaj licencji
Abstrakt (en)
The 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.