In the field of astronomy, it is essential to classify celestial objects like stars, galaxies, and
quasars based on their spectral characteristics. This spectral data provides valuable …

The discipline of astronomy has experienced a substantial metamorphosis due to the advent
of contemporary telescopes, which facilitate the accumulation of extensive spectral …

The heavenly bodies are objects that swim in the outer space. The classification of these
objects is a challenging task for astronomers. This article presents a novel methodology that …

Stellar classification based on spectral characteristics plays a pivotal role in astronomy,
facilitating the study of celestial bodies' composition and evolution. In this research, we …

Abstract Machine learning has achieved great success in many areas today, but the forecast
effect of machine learning often depends on the specific problem. An ensemble learning …

Artificial Intelligence has enabled scientists to rapidly sift through and analyze massive
collections of images, helping to identify objects worthy of closer study such as supernovae …

Machine Learning is used in many fields of study. This paper used machine learning to
classify instances from the Sloan Digital Sky Survey Data Release 17 (SDSS DR17) as a …

In astronomy, classifying celestial objects based on the spectral data observed by
astronomical telescopes is a basic task. So far, most of the work of spectral classification is …

The classification of celestial objects such as stars, galaxies, and quasars is one of
astronomy's most difficult and fundamental problems. Due to the technological advancement …

This study explores the effectiveness of ensemble learning algorithms for accurately
classifying stellar objects in the Gaia DR3 dataset. We compare various classification …