Dr. Ziad Tariq Allawi, a lecturer from the college of engineering, has published a research in the Computation Journal, entitled: )A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq( which is one of the sober academic journals listed in Scopus and Clarivate Analytics databases. This initiative comes in line with the directives of the presidency of the University of Baghdad and the instructions of the deanship of the college of engineering to contribute to raising the status of our educational institution.
In this research, essential parameters of crescent moon sighting were collected from moon sight datasets where they were used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comparison to the actual observational results. ANN simulation gives a clear insight into three crescent moon visibility regions: invisible (I), probably visible (P), and certainly visible (V). The proposed ANN is suitable for building lunar calendars, so it was used to build a four-year calendar on the horizon of Baghdad.
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
