Increasing the Reliability of Flood Embankments with Neural Imaging Method

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Data
2018
Inny tytuł
Typ
Artykuł recenzyjny
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dc.contributor.advisor
Dyscyplina PBN
Informatyka techniczna i telekomunikacja
Czasopismo lub seria
Applied Sciences
ISSN
2076-3417
ISBN
DOI
10.3390/app8091457
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Abstrakt (en)
This 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.
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