Recently, the numerical optimization field has attracted the research community to propose
and develop various metaheuristic optimization algorithms. This paper presents a new …

The difficulty and complexity of the real-world numerical optimization problems has grown
manifold, which demands efficient optimization methods. To date, various metaheuristic …

Objective In this research paper, the brain MRI images are going to classify by considering
the excellence of CNN on a public dataset to classify Benign and Malignant tumors …

Multilevel Thresholding (MLT) is considered as a significant and imperative research field in
image segmentation that can efficiently resolve difficulties aroused while analyzing the …

Feature selection, an optimization problem, becomes an important pre-process tool in data
mining, which simultaneously aims at minimizing feature-size and maximizing model …

This paper proposes a binary version of Horse herd Optimization Algorithm (HOA) to tackle
Feature Selection (FS) problems. This algorithm mimics the conduct of a pack of horses …

A recent meta-heuristic algorithm called Marine Predators Algorithm (MPA) is enhanced
using Opposition-Based Learning (OBL) termed MPA-OBL to improve their search efficiency …

The rapid expansion of information science has caused the issue of “the curse of
dimensionality”, which will negatively affect the performance of the machine learning model …

Feature selection (FS) represents an optimization problem that aims to simplify and improve
the quality of highly dimensional datasets through selecting prominent features and …

The Electrocardiogram (ECG) arrhythmia classification has become an interesting research
area for researchers and developers as it plays a vital role in early prevention and diagnosis …