Incremental Meshfree Approximation of Real Geographic Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43955681" target="_blank" >RIV/49777513:23520/19:43955681 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-21507-1_32" target="_blank" >http://dx.doi.org/10.1007/978-3-030-21507-1_32</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-21507-1_32" target="_blank" >10.1007/978-3-030-21507-1_32</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Incremental Meshfree Approximation of Real Geographic Data

Popis výsledku v původním jazyce

In many technical applications, reconstruction of the scattered data is often task. For big scattered dataset in n-dimensional space, the using some meshless method such as the radial basis function (RBF) approximation is appropriate. RBF approximation is based on the distance computation, and therefore, it is dimensionally non-separable. This approximation can be converted to an overdetermined linear system of equations which has to be solved. A new incremental approach for meshless RBF approximation which respects the significant features of the given terrain data such as break lines is proposed in this paper. Using this approach, the improving approximation of the underlying data is achieved. Moreover, the proposed approach leads to a significant compression of the given dataset and the analytical description of the data is obtained. In comparison with other existing methods, the proposed approach achieves the better results due to respecting the features of the given data.

Název v anglickém jazyce

Incremental Meshfree Approximation of Real Geographic Data

Popis výsledku anglicky

In many technical applications, reconstruction of the scattered data is often task. For big scattered dataset in n-dimensional space, the using some meshless method such as the radial basis function (RBF) approximation is appropriate. RBF approximation is based on the distance computation, and therefore, it is dimensionally non-separable. This approximation can be converted to an overdetermined linear system of equations which has to be solved. A new incremental approach for meshless RBF approximation which respects the significant features of the given terrain data such as break lines is proposed in this paper. Using this approach, the improving approximation of the underlying data is achieved. Moreover, the proposed approach leads to a significant compression of the given dataset and the analytical description of the data is obtained. In comparison with other existing methods, the proposed approach achieves the better results due to respecting the features of the given data.

Druh

D - Stať ve sborníku

CEP obor

—

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

Název statě ve sborníku

Applied Physics, System Science and Computers III

ISBN

978-3-030-21506-4

ISSN

1876-1100

e-ISSN

—

Počet stran výsledku

7

Strana od-do

222-228

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Dubrovnik, Croatia

Datum konání akce

26. 9. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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