Astronomy Then and Now: Using Machine Learning to Validate Ancient Celestial Knowledge
Keywords:
Ancient Astronomy, Machine Learning , Celestial Knowledge, Cultural Heritage, Data ValidationAbstract
Ancient civilizations—from India and Babylon to the Mayans and Greeks—recorded celestial patterns that guided agriculture, navigation, and culture. While rich in empirical observations, much of this knowledge remains untested against modern science. This paper explores how machine learning (ML) can validate and reinterpret ancient astronomical data. Using historical records alongside modern astrophysical datasets, ML models identify patterns, test predictions, and simulate past sky events. Techniques like natural language processing (NLP) also help decode ancient manuscripts. The study highlights how integrating ancient astronomy with ML not only affirms the accuracy of many early observations but also enriches contemporary space research, offering a bridge between cultural heritage and modern science.
DOI: https://doi.org/10.24321/3117.4787.202502
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