The analysis of lunar crescent visibility criterion is vital in providing a comparative insight for predicting the visibility and suitability for Hijri calendar determination. While there have been previous attempts to measure the performance of lunar crescent visibility criterion, these attempts only apply to a singular analysis and not a comparative examination.
Design, Development and Analysis of Lunar Crescent Visibility Criterion with Python explores the development of an analysis tool for lunar crescent visibility criterion using an integrated lunar crescent visibility database. The analysis tool, called HilalPy and HilalObs, was developed in the form of a Python library, so that it can be integrated into other software and webpages to enable deployment into various operating systems. This book will provide useful insights for the future development of lunar crescent visibility criterion, particularly for calendrical purposes.
Key Features:
- Presents an analysis tool for lunar crescent visibility based on an integrated lunar crescent report database
- Offers researchers and practitioners the capability to perform comparative analyses of the percentage of reliability in lunar crescent visibility criteria, thereby contributing to the construction of robust criteria for determining the Hijri calendar
- Provides a comprehensive resource for researchers, students, policymakers, and practitioners involved in the determination of the Hijri calendar
The analysis of lunar crescent visibility criterion is vital in providing a comparative insight for predicting the visibility and suitability for Hijri calendar determination. While there have been previous attempts to measure the performance of lunar crescent visibility criterion, these attempts only apply to a singular analysis and not a comparative examination.
Design, Development and Analysis of Lunar Crescent Visibility Criterion with Python explores the development of an analysis tool for lunar crescent visibility criterion using an integrated lunar crescent visibility database. The analysis tool, called HilalPy and HilalObs, was developed in the form of a Python library, so that it can be integrated into other software and webpages to enable deployment into various operating systems. This book will provide useful insights for the future development of lunar crescent visibility criterion, particularly for calendrical purposes.
Key Features:
- Presents an analysis tool for lunar crescent visibility based on an integrated lunar crescent report database
- Offers researchers and practitioners the capability to perform comparative analyses of the percentage of reliability in lunar crescent visibility criteria, thereby contributing to the construction of robust criteria for determining the Hijri calendar
- Provides a comprehensive resource for researchers, students, policymakers, and practitioners involved in the determination of the Hijri calendar
Design, Development and Analysis of Lunar Crescent Visibility Criterion With Python
144
Design, Development and Analysis of Lunar Crescent Visibility Criterion With Python
144Related collections and offers
Product Details
| ISBN-13: | 9781040224878 |
|---|---|
| Publisher: | CRC Press |
| Publication date: | 12/05/2024 |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| Pages: | 144 |
| File size: | 2 MB |