Results 201 to 210 of about 4,362 (249)

Comprehensive evaluation of optimization algorithms for medical image segmentation. [PDF]

open access: yesSci Rep
Al-Najdawi NA   +4 more
europepmc   +1 more source

An improved Harris Hawks Optimization algorithm for continuous and discrete optimization problems

Engineering Applications of Artificial Intelligence, 2022
Harris Hawks Optimization (HHO) is a population-based meta-heuristic optimization algorithm that has been used for the solution of test functions and real-world problems by many researchers. However, HHO has a premature convergence problem. The main motive of the novel approach in this paper is that the performance of an MHA could be improved by ...
HARUN GEZICI, Haydar Livatyali
exaly   +3 more sources

Modified Harris Hawks Optimization Algorithm for Global Optimization Problems

Arabian Journal for Science and Engineering, 2020
The Harris hawks optimization algorithm (HHO) is a novel swarm-based meta-heuristic algorithm. In this study, a modified Harris hawks optimization algorithm (MHHO) is proposed to enhance the searching performance of the conventional HHO. Past studies have revealed that different adjustment strategies of important variables in meta-heuristic algorithm ...
Xizhao Zhou, Po-Chou Shih
exaly   +2 more sources

A robust multiobjective Harris’ Hawks Optimization algorithm for the binary classification problem

Knowledge-Based Systems, 2021
Abstract The Harris’ Hawks Optimization (HHO) is a recent metaheuristic inspired by the cooperative behavior of the hawks. These avians apply many intelligent techniques like surprise pounce (seven kills) while they are catching their prey according to the escaping patterns of the target.
Tansel Dokeroglu   +2 more
exaly   +2 more sources

A novel quasi-reflected Harris hawks optimization algorithm for global optimization problems

Soft Computing, 2020
Harris hawks optimization (HHO) is a recently developed meta-heuristic optimization algorithm based on hunting behavior of Harris hawks. Similar to other meta-heuristic algorithms, HHO tends to be trapped in low diversity, local optima and unbalanced exploitation ability.
Qian Fan, Zhanghua Xia
exaly   +2 more sources

Home - About - Disclaimer - Privacy