Continuous metaheuristics for binary optimization problems: An updated systematic literature review

M Becerra-Rozas, J Lemus-Romani… - Mathematics, 2022 - mdpi.com
For years, extensive research has been in the binarization of continuous metaheuristics for
solving binary-domain combinatorial problems. This paper is a continuation of a previous …

Parameter extraction of solar photovoltaic models using queuing search optimization and differential evolution

AA Abd El-Mageed, AA Abohany, HMH Saad… - Applied Soft …, 2023 - Elsevier
Given the photovoltaic (PV) model's multi-model and nonlinear properties, extracting its
parameters is a difficult problem to solve. Furthermore, because of the features of the …

Effective feature selection strategy for supervised classification based on an improved binary aquila optimization algorithm

AA Abd El-Mageed, AA Abohany, A Elashry - Computers & Industrial …, 2023 - Elsevier
Feature Selection (FS) is considered a crucial step in machine learning and data mining
tasks, which facilitates minimizing the direct consequence of redundant and irrelevant …

Improved Binary Meerkat Optimization Algorithm for efficient feature selection of supervised learning classification

RM Hussien, AA Abohany, AA Abd El-Mageed… - Knowledge-Based …, 2024 - Elsevier
Feature selection (FS) is a crucial step in machine learning and data mining projects. It aims
to remove redundant and uncorrelated features, thus improving the accuracy of models …

Solving engineering optimization problems based on multi-strategy particle swarm optimization hybrid dandelion optimization algorithm

W Tang, L Cao, Y Chen, B Chen, Y Yue - Biomimetics, 2024 - mdpi.com
In recent years, swarm intelligence optimization methods have been increasingly applied in
many fields such as mechanical design, microgrid scheduling, drone technology, neural …

A Systematic Review of Wind Driven Optimization Algorithms and Their Variants

LL Mao, AM Zain, KQ Zhou, F Qin, FL Wang - IEEE Access, 2024 - ieeexplore.ieee.org
Wind Driven Optimization (WDO) Algorithm is a novel metaheuristic algorithm inspired by
the continuous flow of air resulting from differences in air pressure until the air reaches a …

[PDF][PDF] Deep learning model based on ResNet-50 for beef quality classification

SE Abdallah, WM Elmessery, MY Shams… - Inf. Sci. Lett, 2023 - core.ac.uk
Food quality measurement is one of the most essential topics in agriculture and industrial
fields. To classify healthy food using computer visual inspection, a new architecture was …

A weighted-sum chaotic sparrow search algorithm for interdisciplinary feature selection and data classification

LY Jia, T Wang, AG Gad, A Salem - Scientific Reports, 2023 - nature.com
In today's data-driven digital culture, there is a critical demand for optimized solutions that
essentially reduce operating expenses while attempting to increase productivity. The …

An improved Differential evolution with Sailfish optimizer (DESFO) for handling feature selection problem

SM Azzam, OE Emam, AS Abolaban - Scientific Reports, 2024 - nature.com
As a preprocessing for machine learning and data mining, Feature Selection plays an
important role. Feature selection aims to streamline high-dimensional data by eliminating …

S‐shaped and V‐shaped binary African vulture optimization algorithm for feature selection

K Balakrishnan, R Dhanalakshmi… - Expert …, 2022 - Wiley Online Library
The African vulture optimization algorithm (AVOA) is a recently developed metaheuristic
algorithm that imitates the eating and movement patterns of authentic African vultures. AVOA …