An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection by Abu Zitar, Raed

“…In this paper, a recent swarm intelligence metaheuristic method called RSO which is inspired by the social and hunting behavior of a group of rats is enhanced and explored for FS problems. The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”

Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

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An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications by Abu Zitar, Raed

“…In this review paper, JAYA algorithm, which is a recent population-based algorithm is intensively overviewed. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli (20748758)

“…For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …”

A new genetic algorithm approach for unit commitment by Mantawy, A.H.

“…In the proposed algorithm, coding the solution of the unit commitment problem is based on mixing binary and decimal representations. …”
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Learning-Based Automatic Modulation Classification by Abdelmutalab, Ameen Elsiddig

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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes by Muhammad Mohsin Khan (22150360)

“…We evaluated thirteen machine learning models at each stage, selecting the top-performing classifiers to optimize results. The dataset comprised 535 samples across seven MRS severity levels and was validated using 5-fold cross-validation and diverse subgroups to ensure robust model performance across various scenarios. …”