Abstract The Artificial Gorilla Groups Optimizer (GTO) is a novel metaheuristic algorithm that
takes its cues from the collective intelligence of wild gorilla troops. Although it has shown …

The feature selection (FS) problem has occupied a great interest of scientists lately since the
highly dimensional datasets might have many redundant and irrelevant features. FS aims to …

Hybrid systems have emerged as a reliable solution to meet the increasing demand loads in
various fields and address the electricity shortage in remote areas. Consequently, research …

The jellyfish search (JS) algorithm impersonates the foraging behavior of jellyfish in the
ocean. It is a newly developed metaheuristic algorithm that solves complex and real-world …

In image processing, multi-level thresholding is a sophisticated technique used to delineate
regions of interest in images by identifying intensity levels that differentiate different …

Abstract Hunger Games Search (HGS) is a newly developed swarm-based algorithm
inspired by the cooperative behavior of animals and their hunting strategies to find prey …

Feature selection (FS) constitutes a crucial endeavor in classification procedures, aiming to
identify the minimal subset of features that maximizes classification accuracy. In the realm of …

Water-cycle algorithm based on evaporation rate (ErWCA) is a powerful enhanced version
of the water-cycle algorithm (WCA) metaheuristics algorithm. ErWCA, like other algorithms …

Medical image segmentation is crucial in using digital images for disease diagnosis,
particularly in post-processing tasks such as analysis and disease identification …

Having effective learning and retrieval phases of satisfiability logic in Discrete Hopfield
Neural Network models ensures optimal synaptic weight management, which consequently …