Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Manuel Bullejos"'
Autor:
Manuel Bullejos, Manuel Martín-Martín
Publikováno v:
Journal of Maps, Vol 19, Iss 1 (2023)
ABSTRACTThe goal of this paper is the construction of computerized 3D visualization of geological structures. Several Python applications have been used to adapt the paper map-based geological classical information to numerical geological maps repres
Externí odkaz:
https://doaj.org/article/fed34a48ec2f4f99b74f0df3254fb53e
Autor:
Manuel Bullejos, Manuel Martín-Martín
Publikováno v:
Geosciences, Vol 13, Iss 7, p 207 (2023)
This paper introduces a Python application for visualizing an imbricate thrust system. The application uses the traditional geologic information to create an HTML geological map with real topography and a set of geological cross-sections with the ess
Externí odkaz:
https://doaj.org/article/8263e2a3854b4b07a3d9e4dfc4f4e017
Publikováno v:
Journal of Marine Science and Engineering, Vol 11, Iss 1, p 60 (2023)
In a previous paper, the authors implemented a machine learning k-nearest neighbors (KNN) algorithm and Python libraries to create two 3D interactive models of the stratigraphic architecture of the Quaternary onshore Llobregat River Delta (NE Spain)
Externí odkaz:
https://doaj.org/article/4f7ab828da7f417abc68a447d97cc3ab
Publikováno v:
Journal of Marine Science and Engineering, Vol 10, Iss 7, p 986 (2022)
The k-nearest neighbors (KNN) algorithm is a non-parametric supervised machine learning classifier; which uses proximity and similarity to make classifications or predictions about the grouping of an individual data point. This ability makes the KNN
Externí odkaz:
https://doaj.org/article/9eda368fb98a4b3d83393d691cf9af92
Publikováno v:
Water, Vol 14, Iss 12, p 1882 (2022)
This paper introduces a Python application for visualizing the 3D stratigraphic architecture of porous sedimentary media. The application uses the parameter granulometry deduced from borehole lithological records to create interactive 3D HTML models
Externí odkaz:
https://doaj.org/article/470efffabc65469c97f09b26b63c7af0
Publikováno v:
Estudios de Lingüística, Iss 37, p 23 (2022)
El presente artículo recoge y analiza en 459 lenguas del mundo el número de palabras (tokens) y el número de sonidos y fonemas (unidades fónicas convencionales de token o UFCT) que emplean dichas lenguas para expresar una misma información (en e
Externí odkaz:
https://doaj.org/article/5c18faf28ed04db4ae5e4fe37be98b80
Akademický článek
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Autor:
Martín-Martín, Manuel Bullejos, Manuel
Publikováno v:
Geosciences; Volume 13; Issue 7; Pages: 207
This paper introduces a Python application for visualizing an imbricate thrust system. The application uses the traditional geologic information to create an HTML geological map with real topography and a set of geological cross-sections with the ess
Supplementary data to this article can be found online at https://doi. org/10.1016/j.marpetgeo.2023.106283
This paper introduces a methodology based on Python libraries and machine learning k-Nearest Neighbors (KNN) algorithms to create an inter
This paper introduces a methodology based on Python libraries and machine learning k-Nearest Neighbors (KNN) algorithms to create an inter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23d24be0526d71753f87331591e10c32
https://hdl.handle.net/10481/82427
https://hdl.handle.net/10481/82427
Publikováno v:
Journal of Marine Science and Engineering; Volume 10; Issue 7; Pages: 986
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
The k-nearest neighbors (KNN) algorithm is a non-parametric supervised machine learning classifier; which uses proximity and similarity to make classifications or predictions about the grouping of an individual data point. This ability makes the KNN
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15206d92c9585f0fb84a111f6590c858
https://hdl.handle.net/10045/125553
https://hdl.handle.net/10045/125553