Evolutionary Synthesis of Automatic Classification on Astroinformatic Big Data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F16%3A86099615" target="_blank" >RIV/61989100:27740/16:86099615 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27240/16:86099615
Result on the web
<a href="http://aip.scitation.org/doi/pdf/10.1063/1.4951915" target="_blank" >http://aip.scitation.org/doi/pdf/10.1063/1.4951915</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1063/1.4951915" target="_blank" >10.1063/1.4951915</a>

Result language
angličtina
Original language name
Evolutionary Synthesis of Automatic Classification on Astroinformatic Big Data
Original language description
This article describes the initial experiments using a new approach to automatic identification of Be and B[e] stars spectra in large archives. With enormous amount of these data it is no longer feasible to analyze it using classical approaches. We introduce an evolutionary synthesis of the classification by means of analytic programming, one of methods of symbolic regression. By this method, we synthesize the most suitable mathematical formulas that approximate chosen samples of the stellar spectra. As a result is then selected the category whose formula has the lowest difference compared to the particular spectrum. The results show us that classification of stellar spectra by means of analytic programming is able to identify different shapes of the spectra.
Czech name
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Czech description
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Project
<a href="/en/project/GA15-06700S" target="_blank" >GA15-06700S: Unconventional Control of Complex Systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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