Toward a globally lunar calendar: a machine learning-driven approach for crescent moon visibility prediction

Abstract This paper presents a comprehensive approach to harmonizing lunar calendars across different global regions, addressing the long-standing challenge of variations in new crescent Moon sightings that mark the beginning of lunar months. We propose a machine learning (ML)-based framework to pre...

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Hauptverfasser:	Samia Loucif, Murad Al-Rajab, Raed Abu Zitar, Mahmoud Rezk
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	SpringerOpen 2024-08-01
Schriftenreihe:	Journal of Big Data
Schlagworte:	Crescent visibility Machine learning Lunar calendar Prediction Hyperparameter tuning Feature selection
Online-Zugang:	https://doi.org/10.1186/s40537-024-00979-6
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