Predicting the Visibility of the First Crescent

Predicting the Visibility of the First Crescent


  • Tafseer Ahmed Mohammad Ali Jinnah University, Pakistan



crescent visibility, astronomy, supervised learning, feature engineering, ensemble


This study presents an application of machine learning to predict whether the first crescent of the lunar month will be visible to naked eye on a given date. The study presents a dataset of successful and unsuccessful attempts to find the first crescent at the start of the lunar month. Previously, this problem was solved by analytically deriving the equations for visibility parameter(s) and manually fixing threshold values. However, we applied supervised machine learning on the independent variables of the problem, and the system learnt about the criteria of classification. The system gives precision of 0.88 and recall of 0.87 and hence it treats both false positives and false negatives equally well.


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