[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119790-en":3,"doc-seo-119790-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119790,962075006959,"Anda","https://ap-avatar.wpscdn.com/avatar/e0002397efbe92a78e?_k=1776741047341049297",8,"Research & Report","Predicting new crescent moon visibility applying machine learning algorithms","Muslim countries rely on the Hijri lunar calendar, where each month begins with the first sighting of a new crescent Moon, yet communities lack consensus on the start of Ramadan. Differences stem from imprecise local observations influenced by sky conditions, observing tools, observer skill, and location. The study proposes machine learning methods to predict new crescent Moon visibility and thereby support more consistent Ramadan start decisions. Experimental results show strong predictive accuracy, with Random Forest and Support Vector Machine outperforming other classifiers.","Zayed University  \nZU Scholars  \nAll Works  \n12-1-2023  \nPredicting new crescent moon visibility applying machine learning algorithms  \nMurad Al-Rajab Abu Dhabi University  \nSamia Loucif Zayed University  \nYazan Al Risheh Abu Dhabi University  \nFollow this and additional works at: [https://zuscholars.zu.ac.ae/works](https://zuscholars.zu.ac.ae/works)  \n Part of the Computer Sciences Commons  \nRecommended Citation  \nAl-Rajab, Murad; Loucif, Samia; and Al Risheh, Yazan, \"Predicting new crescent moon visibility applying machine learning algorithms\" (2023) . All Works. 5841.  \n[https://zuscholars.zu.ac.ae/works/5841](https://zuscholars.zu.ac.ae/works/5841)  \nThis Article is brought to you for free and open access by ZU Scholars. It has been accepted for inclusion in All Works by an authorized administrator of ZU Scholars. For more information, please contact [scholars@zu.ac.ae](scholars@zu.ac.ae).  \n[www. nature.com/scientificreports](www. nature.com/scientificreports)  \nOPEN  \nPredicting new crescent moon visibility applying machine learning algorithms  \nMurad Al‑Rajab1*, Samia Loucif2 & YazanAl Risheh1  \nThe 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.  \nTill today, there is no consensus on deciding on the beginning of Ramadan month within the Muslim community. This is mainly duetothe 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  \nMoon.  \nIslam is considered the second religion in the world. Hijri is the Islamic calendar, also known as the lunar Hijri calendar. This is because each month starts in the Hijri calendar when the new crescent Moon is first sighted after the birth of a new Moon. Although almost all countries in the world use the Gregorian calendar for easy communication, The Hijri calendar is used by Muslim countries and Muslims, in general, across the world when it comes to religious events. Ramadan is among the holy months for Muslims. Deciding on the start of Ramadan has always been a challenging mission, and as a result, not all Muslims start Ramadan synchronously. The main reason is due to the reliance on individuals’ observations of the new crescent Moon which depends on several factors that affect the final results, such as the tools used for Moon observation, sky status whether clear or cloudy, the location from where the observation is conducted, the proficiency of the observers, etc.  \nFurthermore, with technological advancement, there are controversial opinions on whether to use the eye sighting of the new crescent Moon or astronomical calculation methods. The problem becomes even more serious given the number of Muslims worldwide who, each time Ramadan approaches, wait for the announcement of the first day of Ramadan. The latter is the ninth month in the Hijri calendar, and during this month, Muslim fast from before Sunrise till Sunset. Additionally, there is a need for a consensus on that day among all Muslims in the world. According to1 and2, and as indicated in F","cbCaimUfuDUpuEa9","https://ap.wps.com/l/cbCaimUfuDUpuEa9","pdf",3036462,1,16,"English","en",105,"# Introduction\n## Hijri calendar and crescent visibility\n## Challenge in deciding Ramadan start\n## Observational factors and technological debate\n# Proposed approach\n## Machine learning for visibility prediction\n# Results and evaluation\n## Random Forest and SVM performance","[{\"question\":\"Why is there no consensus on the beginning of Ramadan?\",\"answer\":\"The beginning of Ramadan varies due to imprecise observations of the new crescent Moon across different locations and conditions, which depend on tools, sky clarity, location, and observer proficiency.\"},{\"question\":\"How does the paper use machine learning for Ramadan start prediction?\",\"answer\":\"It proposes using machine learning algorithms to predict the visibility of the new crescent Moon, using this prediction to support determining the start of Ramadan more consistently.\"},{\"question\":\"Which classifiers performed best in the experiments?\",\"answer\":\"The Random Forest and Support Vector Machine classifiers delivered promising results and strong prediction accuracy compared with other classifiers tested.\"}]","Predicting new crescent moon visibility applying machine learning algorithms | 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is there no consensus on the beginning of Ramadan?","Question",{"text":75,"@type":76},"The beginning of Ramadan varies due to imprecise observations of the new crescent Moon across different locations and conditions, which depend on tools, sky clarity, location, and observer proficiency.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the paper use machine learning for Ramadan start prediction?",{"text":80,"@type":76},"It proposes using machine learning algorithms to predict the visibility of the new crescent Moon, using this prediction to support determining the start of Ramadan more consistently.",{"name":82,"@type":73,"acceptedAnswer":83},"Which classifiers performed best in the experiments?",{"text":84,"@type":76},"The Random Forest and Support Vector Machine classifiers delivered promising results and strong prediction accuracy compared with other classifiers 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