Efficient Simple Large Scattered 3D Vector Fields Radial Basis Functions Approximation Using Space Subdivision
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43955678" target="_blank" >RIV/49777513:23520/19:43955678 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-24289-3_25" target="_blank" >http://dx.doi.org/10.1007/978-3-030-24289-3_25</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-24289-3_25" target="_blank" >10.1007/978-3-030-24289-3_25</a>
Alternative languages
Result language
angličtina
Original language name
Efficient Simple Large Scattered 3D Vector Fields Radial Basis Functions Approximation Using Space Subdivision
Original language description
The Radial basis function (RBF) approximation is an efficient method for scattered scalar and vector data fields. However its application is very difficult in the case of large scattered data. This paper presents RBF approximation together with space subdivision technique for large vector fields. For large scattered data sets a space subdivision technique with overlapping 3D cells is used. Blending of overlapped 3D cells is used to obtain continuity and smoothness. The proposed method is applicable for scalar and vector data sets as well. Experiments proved applicability of this approach and results with the tornado large vector field data set are presented.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA17-05534S" target="_blank" >GA17-05534S: Meshless methods for large scattered spatio-temporal vector data visualization</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Computational Science and Its Applications – ICCSA 2019
ISBN
978-3-030-24288-6
ISSN
0302-9743
e-ISSN
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Number of pages
14
Pages from-to
337-350
Publisher name
Springer
Place of publication
Cham
Event location
Saint Petersburg University, Saint Petersburg
Event date
Jul 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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