The use of computational intelligence models for multi-step time series forecasting tasks has
presented satisfactory results in such a way that they are considered models with an …

Abstract Characterization, correlation and provenance determination of tephra samples in
sedimentary sections (tephrochronological studies) are powerful tools for establishing ages …

Wide-angle photometric surveys of previously uncharted sky areas or wavelength regimes
will always bring in unexpected sources–novelties or even anomalies–whose existence and …

This paper follows series of our works on the applicability of various machine learning
methods to the morphological galaxy classification (Vavilova et al., 2021, 2022). We …

We propose a new soft clustering scheme for classifying galaxies in different activity classes
using simultaneously four emission-line ratios: log ([]/H α), log ([]/H α), log ([]/H α), and log …

The spectrum of a galaxy contains information about its physical properties. Classifying
spectra using templates helps to elucidate the nature of a galaxy's energy sources. In this …

Spectral classification of emission-line galaxies (ELGs) plays an important role to
understand the formation and evolution of different galaxies. Machine learning can obtain …

This paper presents a robust neural network approach for identifying hot subdwarfs. Our
method leveraged the Squeeze-and-Excitation Residual Network to extract abstract …

Hot subdwarf stars are core He burning stars located at the blue end of the horizontal
branch, which is also known as the extreme horizontal branch. The spectra of hot subdwarf …

Stellar spectral classification is one of the most fundamental tasks in survey astronomy.
Many automated classification methods have been applied to spectral data. However, their …