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Increasing the Reliability of Flood Embankments with Neural Imaging Method

cris.lastimport.scopus2024-09-19T01:30:58Z
dc.abstract.enThis paper presents an innovative system of many artificial neural networks that enables the tomographic reconstruction of the internal structure of a flood embankment. An advantage of the proposed method is that it allows us to obtain high-resolution images, which essentially contributes to early, precise and reliable prediction of operational hazards. The method consists in training a cluster of separate neural networks, each of which generates a single point of the output image. The simultaneous and parallel application of the set of neural networks led to effective reconstruction of the internal structure of a deposition site for floatation tailings. Results obtained from the study allow us to solve the low resolution problem that usually occurs with non-invasive imaging methods. This effect was possible thanks to the design of a new intelligent image reconstruction system.
dc.affiliationTransportu i Informatyki
dc.contributor.authorGrzegorz Kłosowski
dc.contributor.authorTomasz Rymarczyk
dc.contributor.authorArkadiusz Gola
dc.date.accessioned2024-05-09T08:48:18Z
dc.date.available2024-05-09T08:48:18Z
dc.date.issued2018
dc.identifier.doi10.3390/app8091457
dc.identifier.issn2076-3417
dc.identifier.urihttps://repo.akademiawsei.eu/handle/item/297
dc.languageen
dc.pbn.affiliationinformation and communication technology
dc.relation.ispartofApplied Sciences
dc.rightsCC-BY
dc.subject.enelectrical tomography
dc.subject.enflood embankments
dc.subject.enneural networks
dc.subject.ennumerical modeling
dc.titleIncreasing the Reliability of Flood Embankments with Neural Imaging Method
dc.typeReviewArticle
dspace.entity.typePublication
oaire.citation.issue9
oaire.citation.volume8