Application of optimization heuristics for complex astronomical object model identification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F16%3A43897731" target="_blank" >RIV/60461373:22340/16:43897731 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/content/pdf/10.1007%2Fs00500-014-1527-y.pdf" target="_blank" >http://link.springer.com/content/pdf/10.1007%2Fs00500-014-1527-y.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00500-014-1527-y" target="_blank" >10.1007/s00500-014-1527-y</a>
Alternative languages
Result language
angličtina
Original language name
Application of optimization heuristics for complex astronomical object model identification
Original language description
Detection and localization of astronomical objects are two of the most fundamental topics in astronomical science where localization uses detection results. Object localization is based on modeling of point spread function and estimation of its parameters. Commonly used models as Gauss or Moffat in objects localization provide good approximation of analyzed objects but cannot be sufficient in the case of exact applications such as object energy estimation. Thus the use of sophisticated models is upon the place. One of the key roles plays also the way of the objective function estimation. The least square method is often used, but it expects data with normal distribution, thus there is a question of a maximum likelihood method application. Another important factor of presented problem is choice of the right optimization method. Classical methods for objective function minimization usually require a good initial estimate for all parameters and differentiation of the objective function with respect to model parameters. The results indicated that stochastic methods such as simulated annealing or harmony search achieved better results than the classical optimization methods.
Czech name
—
Czech description
—
Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
—
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Soft Computing
ISSN
1433-7479
e-ISSN
—
Volume of the periodical
20
Issue of the periodical within the volume
2
Country of publishing house
DE - GERMANY
Number of pages
16
Pages from-to
621-636
UT code for WoS article
000372297200014
EID of the result in the Scopus database
2-s2.0-84955660382