Algorithm for placement of reference points and choice of an appropriate variable shape parameter for the RBF approximation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43957171" target="_blank" >RIV/49777513:23520/20:43957171 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.3233/ICA-190610" target="_blank" >https://doi.org/10.3233/ICA-190610</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/ICA-190610" target="_blank" >10.3233/ICA-190610</a>

Result language

angličtina

Original language name

Algorithm for placement of reference points and choice of an appropriate variable shape parameter for the RBF approximation

Original language description

Many Radial Basis Functions (RBFs) contain a shape parameter which has an important role to ensure good quality of the RBF approximation. Determination of the optimal shape parameter is a difficult problem. In the majority of papers dealing with the RBF approximation, the shape parameter is set up experimentally or using some ad-hoc method. Moreover, the constant shape parameter is almost always used for the RBF approximation, but the variable shape parameter produces more accurate results. Several variable shape parameter methods, which are based on random strategy or on an evolutionary algorithm, have been developed. Another aspect which has an influence on the quality of the RBF approximation is the placement of reference points. A novel algorithm for finding an appropriate set of reference points and a variable shape parameter selection for the RBF approximation of functions y=f(x) (i.e. the case when a one-dimensional dataset is given and each point from this dataset is associated with a scalar value) is presented. Our approach has two steps and is based on exploiting features of the given dataset, such as extreme points or inflection points, and on comparison of the first curvature of a curve. The proposed algorithm can be used for the approximation of data describing a curve parameterized by one variable in multidimensional space, e.g. a robot path planning, etc.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

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)

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)

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Integrated Computer-Aided Engineering

ISSN

1069-2509

e-ISSN

—

Volume of the periodical

27

Issue of the periodical within the volume

1

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

15

Pages from-to

1-15

UT code for WoS article

000500958600001

EID of the result in the Scopus database

2-s2.0-85076343808