College of Computer Science and Mathematics

Discussion of a master’s thesis in the College of Computer Science and Mathematics – Department of Statistics and InformaticsAt the Faculty of Computer Science and Mathematics at the University of Mosul, a master’s thesis entitled (Estimation of missing values ​​for air pollution time series data using hybrid methods for recurrent and cloudy neural networks) was discussed for the student Moamen Amer Hassan Al-Sayegh, under the supervision of the teacher, Dr. Osama Bashir Al-Hanoon.The thesis aimed to reach the best results with the least errors in computing the missing values ​​of the data of the dependent variable PM10, which corresponds to many atmospheric pollutants as explanatory variables. Many traditional and intelligent methods have been used to achieve the best results, including the multiple linear regression model (MLR) as a traditional statistical method commonly used, recursive neural networks (RNNs), as well as the adaptive inferential fuzzy nervous system (ANFIS) as intelligent methods used for the purpose of improving the results of calculating the missing values ​​of the dependent variable.The discussion committee consisted of:
1. Prof. Dr. Taha Hussein Ali – Chairman
2. Assis.Prof. Dr. Haifa Abdel-Gawad Saeed – Member
3. Assit.Prof. Dr. Safwan Omar Hassoun – Member
4. Dr. Osama Bashir Al-Hanoun – Member and SupervisorThe student obtained a master’s degree in statistics.