master’s thesis of the student, Lubna Jamal Chachan Khurshid
In continuation of the scientific research movement and with the follow-up and presence of the respected Dean of the College of Computer Science and Mathematics, Professor Dr. Duha Bashir Abdullah.
On Sunday 9/10/2023, the master’s thesis of the student, Lubna Jamal Chachan Khurshid, was discussed in the discussion hall at the College of Computer Science and Mathematics at the University of Mosul, under the supervision of Assist.Prof. Baydaa Sulaiman Bahnam
The thesis submitted by the student dealt with the use of four algorithms: RF machine learning algorithm, three deep learning algorithms (LSTM, Bi_LSTM, GRU) to predict the monthly suspended sediment load (SSL) on the dataset of the Great Zab River in Iraq. The proposed models were trained and tested by building and applying seven scenarios that included different inputs for this data in order to find the most efficient and accurate predictive model by making several comparisons using evaluation Metrics.
The study aims at the contribution of the proposed model as an applied research for water resources management and specialists in this field to predict the monthly suspended sediment load of the Greater Zab River using deep and machine learning algorithms, which ensures the success of monitoring to reduce losses and risks of potential damage from these sediments.
The scientific committee included the following members:
- Dr. Ibrahim Ahmed Saleh (University of Mosul) / Chief
- Dr. Shahba Ibrahim Khalil (University of Mosul) / Member
- Associate. Prof. Dr. Mohammed Chachan Younis (University of Mosul) / member
- Associate. Prof. Baydaa Sulaiman Bahnam (University of Mosul) / member and supervisor