As technologies and sciences evolve, they produce large amounts of data curated in complex datasets that must be analyzed. The big-data phenomenon corresponds to the new times and advances that create new sources with voluminous datasets that require processing and management. Specifically, in astronomy, data comes from various telescopes, space missions, photographs, spectroscopy, historical records, and other sources. Collected data can be used for further developments and theories regarding planet formation and predictions for the future. However, instead of traditional data processing methods like manual or statistical analysis, machine learning and artificial intelligence (AI) can be a solution to performing unsupervised learning to find hidden patterns within the data. Applying machine learning techniques and implementing AI algorithms in the analysis of astronomical data collected from various sources will lead to the discovery of previously unrecognized patterns and relationships within data, hence increasing our understanding of the planet and galaxy formations and facilitating more accurate predictions of celestial bodies and the universe.

Authors: Sofia Toropova, Aspen Olmsted

Published in: International Conference for Internet Technology and Secured Transactions (ICITST-2023)

• Date of Conference: 13-15 November 2023
• DOI: 10.20533/ICITST.2023.0015
• ISBN: 978-1-913572-63-1
• Conference Location: St Anne’s College, Oxford University, UK