An Information Technology Center Lecturer publishes scientific research in a respected international journal

The Journal of Supercomputing, affiliated with Springer Publishing, was published with an impact factor of 3.3

Scientific research entitled:

“BCDDO: Binary Child Drawing Development Optimization”

Submitted by researcher asst.L. Abu Bakr Saeb Issa, a lecturer at the Information Technology Center

The research aimed to create a binary version (BCDDO) of the Child Drawing Development Optimization (CDDO) algorithm to improve classification accuracy by selecting important features from the data. 

The results extracted from the research indicate that the binary version, BCDDO, has provided a noticeable improvement in classification accuracy compared to other optimization algorithms studied, such as (Harris Hawk optimization, salp swarm optimization, bat) and others, on a set of different data.

For example, a classification accuracy of up to 99.36% was achieved on the big COVID dataset using XGBoost classification after using BCDDO for feature selection. These results show promising effectiveness of using BCDDO in improving the performance of classification models through selecting appropriate features.