3D vector field approximation and critical points reduction using radial basis functions

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43961717" target="_blank" >RIV/49777513:23520/19:43961717 - isvavai.cz</a>
Výsledek na webu
<a href="http://www.naun.org/main/NAUN/mechanics/2019/a262003-acf.pdf" target="_blank" >http://www.naun.org/main/NAUN/mechanics/2019/a262003-acf.pdf</a>
DOI - Digital Object Identifier
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Jazyk výsledku
angličtina
Název v původním jazyce
3D vector field approximation and critical points reduction using radial basis functions
Popis výsledku v původním jazyce
Vector field simplification aims to reduce the complexity of the flow by removing features according to their relevance and importance. However, the important features as critical points with a large range of influence should be preserved. We present a new approach for vector field simplification and approximation using Radial basis functions. The experiments proved the ability to approximate complex 3D tornado data set. In addition, a significant contribution of the proposed method is also an analytical form of the vector field which can be used in further processing.
Název v anglickém jazyce
3D vector field approximation and critical points reduction using radial basis functions
Popis výsledku anglicky
Vector field simplification aims to reduce the complexity of the flow by removing features according to their relevance and importance. However, the important features as critical points with a large range of influence should be preserved. We present a new approach for vector field simplification and approximation using Radial basis functions. The experiments proved the ability to approximate complex 3D tornado data set. In addition, a significant contribution of the proposed method is also an analytical form of the vector field which can be used in further processing.

Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
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OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt
<a href="/cs/project/GA17-05534S" target="_blank" >GA17-05534S: Meshless metody pro vizualizaci velkých časově-prostorových vektorových dat</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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