Recent advances in harris hawks optimization: A comparative study and applications
The Harris hawk optimizer is a recent population-based metaheuristics algorithm that
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
Performance optimization of differential evolution with slime mould algorithm for multilevel breast cancer image segmentation
Breast cancer is one of the most dangerous diseases for women's health, and it is imperative
to provide the necessary diagnostic assistance for it. The medical image processing …
to provide the necessary diagnostic assistance for it. The medical image processing …
Random following ant colony optimization: Continuous and binary variants for global optimization and feature selection
X Zhou, W Gui, AA Heidari, Z Cai, G Liang… - Applied Soft Computing, 2023 - Elsevier
Continuous ant colony optimization was a population-based heuristic search algorithm
inspired by the pathfinding behavior of ant colonies with a simple structure and few control …
inspired by the pathfinding behavior of ant colonies with a simple structure and few control …
Adaptive Harris hawks optimization with persistent trigonometric differences for photovoltaic model parameter extraction
In this paper, an adaptive Harris hawk optimization with persistent trigonometric (sine–
cosine)-differences (ADHHO) is proposed for parameter identification of Photovoltaic (PV) …
cosine)-differences (ADHHO) is proposed for parameter identification of Photovoltaic (PV) …
Enhanced Harris hawks optimization with multi-strategy for global optimization tasks
Abstract Harris Hawks Optimization (HHO) algorithm is a newly proposed meta-heuristic
optimization algorithm that simulates the hunting process of the Harris hawks. It has the …
optimization algorithm that simulates the hunting process of the Harris hawks. It has the …
Elitist non-dominated sorting Harris hawks optimization: Framework and developments for multi-objective problems
This paper proposed a novel multi-objective non-sorted Harris Hawks Optimizer (NSHHO)
part of the recently developed Harris Hawks Optimizer (HHO) based on an elitist non …
part of the recently developed Harris Hawks Optimizer (HHO) based on an elitist non …
Optimizing energy consumption patterns of smart home using a developed elite evolutionary strategy artificial ecosystem optimization algorithm
In recent times, the tremendous progress in electronic devices and making them available to
all consumers has led to an increase in demand for energy, the formation of a peak, and an …
all consumers has led to an increase in demand for energy, the formation of a peak, and an …
Memory-based Harris hawk optimization with learning agents: a feature selection approach
Feature selection is a vital pre-processing phase for most machine learning and data mining
courses. This article proposes new variants of the Harris hawk optimization called memory …
courses. This article proposes new variants of the Harris hawk optimization called memory …
The hybrid Harris hawks optimizer-arithmetic optimization algorithm: A new hybrid algorithm for sizing optimization and design of microgrids
This paper presents a new hybrid metaheuristic algorithm, the hybrid Harris Hawks
Optimizer-Arithmetic Optimization Algorithm (hHHO-AOA), as we have named it. It is …
Optimizer-Arithmetic Optimization Algorithm (hHHO-AOA), as we have named it. It is …
A self-adaptive quantum equilibrium optimizer with artificial bee colony for feature selection
Feature selection (FS) is a popular data pre-processing technique in machine learning to
extract the optimal features to maintain or increase the classification accuracy of the dataset …
extract the optimal features to maintain or increase the classification accuracy of the dataset …