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Surface Mapping of Earth-like Exoplanets using Single Point Light Curves

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Published on: May 10, 2020

Predicting new crescent moon visibility applying machine learning algorithms.

Murad Al-Rajab¹, Samia Loucif², Yazan Al Risheh³

¹College of Engineering, Abu Dhabi University, Abu Dhabi, UAE. murad.al-rajab@adu.ac.ae.

Scientific Reports

|April 24, 2023

Summary

This summary is machine-generated.

Machine learning accurately predicts new crescent Moon visibility to determine the start of Ramadan. This AI approach addresses challenges in lunar observations for the Islamic calendar, aiding religious event timing.

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Area of Science:

Computational Astronomy
Islamic Studies
Artificial Intelligence

Background:

The global Muslim population is rapidly increasing, necessitating accurate determination of Islamic calendar events.
The Hijri (Islamic lunar) calendar relies on new crescent Moon observation, leading to discrepancies in determining key dates like Ramadan.
Current methods for lunar observation are imprecise, causing a lack of consensus within the Muslim community.

Purpose of the Study:

To propose and evaluate machine learning algorithms for predicting new crescent Moon visibility.
To enhance the accuracy and consistency of determining the start of Ramadan and other Islamic lunar months.

Main Methods:

Utilized machine learning algorithms, including Random Forest and Support Vector Machine classifiers.
Trained and tested models on data related to new crescent Moon visibility.
Compared the performance of various classifiers for prediction accuracy.

Main Results:

Machine learning models demonstrated very good prediction and evaluation performance.
Random Forest and Support Vector Machine classifiers showed particularly promising results.
The study achieved accurate predictions for new Moon visibility, crucial for lunar calendar events.

Conclusions:

Machine learning offers a viable and accurate solution for predicting new crescent Moon visibility.
This AI-driven approach can help resolve the lack of consensus in determining the start of Ramadan.
The findings support the integration of AI in astronomical calculations for religious observances.