A systematic review on metaheuristic optimization techniques for feature selections in disease diagnosis: open issues and challenges
There is a need for some techniques to solve various problems in today's computing world.
Metaheuristic algorithms are one of the techniques which are capable of providing practical …
Metaheuristic algorithms are one of the techniques which are capable of providing practical …
RETRACTED ARTICLE: Group search optimizer: a nature-inspired meta-heuristic optimization algorithm with its results, variants, and applications
L Abualigah - Neural Computing and Applications, 2021 - Springer
In this paper, to keep the researchers interested in nature-inspired algorithms and
optimization problems, a comprehensive survey of the group search optimizer (GSO) …
optimization problems, a comprehensive survey of the group search optimizer (GSO) …
Aquila optimizer: a novel meta-heuristic optimization algorithm
This paper proposes a novel population-based optimization method, called Aquila Optimizer
(AO), which is inspired by the Aquila's behaviors in nature during the process of catching the …
(AO), which is inspired by the Aquila's behaviors in nature during the process of catching the …
Review and empirical analysis of sparrow search algorithm
Y Yue, L Cao, D Lu, Z Hu, M Xu, S Wang, B Li… - Artificial Intelligence …, 2023 - Springer
In recent years, swarm intelligence algorithms have received extensive attention and
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …
Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy
D Zhao, L Liu, F Yu, AA Heidari, M Wang… - Knowledge-Based …, 2021 - Elsevier
Although the continuous version of ant colony optimizer (ACOR) has been successfully
applied to various problems, there is room to boost its stability and improve convergence …
applied to various problems, there is room to boost its stability and improve convergence …
A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments
Efficient task scheduling is considered as one of the main critical challenges in cloud
computing. Task scheduling is an NP-complete problem, so finding the best solution is …
computing. Task scheduling is an NP-complete problem, so finding the best solution is …
A novel evolutionary arithmetic optimization algorithm for multilevel thresholding segmentation of covid-19 ct images
One of the most crucial aspects of image segmentation is multilevel thresholding. However,
multilevel thresholding becomes increasingly more computationally complex as the number …
multilevel thresholding becomes increasingly more computationally complex as the number …
A two‐stream deep neural network‐based intelligent system for complex skin cancer types classification
Medical imaging systems installed in different hospitals and labs generate images in bulk,
which could support medics to analyze infections or injuries. Manual inspection becomes …
which could support medics to analyze infections or injuries. Manual inspection becomes …
Amended hybrid multi-verse optimizer with genetic algorithm for solving task scheduling problem in cloud computing
L Abualigah, M Alkhrabsheh - The Journal of Supercomputing, 2022 - Springer
The central cloud facilities based on virtual machines offer many benefits to reduce the
scheduling costs and improve service availability and accessibility. The approach of cloud …
scheduling costs and improve service availability and accessibility. The approach of cloud …
Harris hawks optimization algorithm: variants and applications
This paper introduces a comprehensive survey of a new swarm intelligence optimization
algorithm so-called Harris hawks optimization (HHO) and analyzes its major features. HHO …
algorithm so-called Harris hawks optimization (HHO) and analyzes its major features. HHO …