Discussion of a master's dissertation in the College of Computer Science and Mathematics - Department of Mathematics entitled "Improving Intelligent Numerical Optimization Algorithms to Distinguish Patterns"

A master's dissertation was discussed in the discussion hall of the Faculty of Computer Science and Mathematics at the University of Mosul on Sunday 12/9/2021 on Improving Intelligent Numerical Optimization Algorithms to Discriminate Patterns by Nour Maan Abdul-Jabbar Younes, under the supervision of Prof. Dr. Ban Ahmed Hassan.

The dissertation dealt with the study of two post-intuitive algorithms, namely the flame moth examples algorithm (MFOA) and the chimpanzee examples algorithm ChOA, and their hybridization with one of the classical algorithms, the conjugate gradient algorithm (CGA) that improves the randomly generated elementary population.

The dissertation dealt with the adoption of an application based on verifying the identity of the person using the hybrid algorithm ChOA in order to distinguish patterns. About 50 samples were taken for different people, and for each sample (12) pictures were taken under different conditions (in terms of lighting and different angles), to enter those pictures into several stages in terms of processing, training and extracting characteristics.

The dissertation aimed at examining the images by the Perform, as it shows us the success of the proposed application when working in the two phases of identifying people and verifying the identity of the person, as a very good discrimination rate was obtained through the FAR and GAR scales.

The discussion committee was chaired by Prof. Dr. Omar Saber Qassem, with the membership of Assistant Professor Dr. Nizar Khalaf Hussain from Tikrit University and Assistant Professor Dr. Ibrahim Ahmed Saleh, with membership and supervision by Prof. Dr. Ban Ahmed Hassan Mitras.

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