The new hilaal visibility criterion for tropical region

Utama, Judhistira Aria; Simatupang, Florian; Amsor,

doi:10.1088/1742-6596/1280/2/022073

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…Also, he claimed that the crescent, whose elongation was less than Danjon's limit, could be seen through a 120 mm telescope. Utama et al [21] used 𝐴𝑅𝐶𝐿 and 𝐴𝑅𝐶𝑉 to develop a criterion for moon sighting using an observation dataset held in Malaysia. He found that the minimum 𝐴𝑅𝐶𝑉 was 8.4° and the minimum 𝐴𝑅𝐶𝐿 was 7.1°.…”

Section: Related Workmentioning

confidence: 99%

Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network

Allawi

2024

Iraqi Journal of Science

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Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certainly visible. This criterion was used on the dataset for ANN learning to compare its efficiency with the actual moon visibility events.

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Section: Related Workmentioning

confidence: 99%

Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network

Allawi

2024

Iraqi Journal of Science

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“… ARCL, the ARC of the Light, also known as elongation, is defined as the angular distance between the Moon and the Sun 13 . ARCL is also used to calculate the width of the crescent Moon, W. The Azimuth' of an object defines its position on the celestial sphere in the horizontal coordinate system, measured in degrees starting from 0 north and turning in a clockwise direction 14 , as shown in Fig. 4 .…”

Section: Introductionmentioning

confidence: 99%

“…The Azimuth' of an object defines its position on the celestial sphere in the horizontal coordinate system, measured in degrees starting from 0 north and turning in a clockwise direction 14 , as shown in Fig. 4 .…”

Section: Introductionmentioning

confidence: 99%

Predicting new crescent moon visibility applying machine learning algorithms

Al-Rajab

Loucif

Risheh

2023

Sci Rep

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The world's population is projected to grow 32% in the coming years, and the number of Muslims is expected to grow by 70%—from 1.8 billion in 2015 to about 3 billion in 2060. Hijri is the Islamic calendar, also known as the lunar Hijri calendar, which consists of 12 lunar months, and it is tied to the Moon phases where a new crescent Moon marks the beginning of each month. Muslims use the Hijri calendar to determine important dates and religious events such as Ramadan, Haj, Muharram, etc. Till today, there is no consensus on deciding on the beginning of Ramadan month within the Muslim community. This is mainly due to the imprecise observations of the new crescent Moon in different locations. Artificial intelligence and its sub-field machine learning have shown great success in their application in several fields. In this paper, we propose the use of machine learning algorithms to help in determining the start of Ramadan month by predicting the visibility of the new crescent Moon. The results obtained from our experiments have shown very good accurate prediction and evaluation performance. The Random Forest and Support Vector Machine classifiers have provided promising results compared to other classifiers considered in this study in predicting the visibility of the new Moon.

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The new hilaal visibility criterion for tropical region

Cited by 2 publications

References 2 publications

Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network

Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network

Predicting new crescent moon visibility applying machine learning algorithms

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