Improved War Strategy Optimization Algorithm

Version 1.0.0 (7,54 ko) par I. Berkan Aydilek

Improved War Strategy Optimization with A Novel Random Opposition-Based Learning

Suivre

0.0

(0)

88 téléchargements

Mise à jour 29 juin 2025

Afficher la licence

% Improved War Strategy Optimization with A Novel Random Opposition-Based Learning

% Please cite:

% Aydilek, İ.B.; Uslu, A.; Kına, C. Improved War Strategy Optimization with Extreme Learning Machine for Health Data Classification. Appl. Sci. 2025, 15, 5435. https://doi.org/10.3390/app15105435

% usage -> [King_fit, King,Convergence_curve] = IWSO(populationSize,Max_iteration,lb,ub,dim,fobj)

Citation pour cette source

Aydilek, İbrahim Berkan, et al. “Improved War Strategy Optimization with Extreme Learning Machine for Health Data Classification.” Applied Sciences, vol. 15, no. 10, May 2025, p. 5435, https://doi.org/10.3390/app15105435.

Afficher d’autres styles

Compatibilité avec les versions de MATLAB

Créé avec R2022a

Compatible avec toutes les versions

Plateformes compatibles

Windows macOS Linux

Tags Ajouter des tags

Remerciements

Inspiré par : War Strategy Optimization Algorithm for MATLAB

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Version	Publié le	Notes de version
1.0.0	29 juin 2025		Télécharger

MLA	Aydilek, İbrahim Berkan, et al. “Improved War Strategy Optimization with Extreme Learning Machine for Health Data Classification.” Applied Sciences, vol. 15, no. 10, May 2025, p. 5435, https://doi.org/10.3390/app15105435.
APA	Aydilek, İ. B., Uslu, A., & Kına, C. (2025). Improved War Strategy Optimization with Extreme Learning Machine for Health Data Classification. Applied Sciences, 15(10), 5435. MDPI AG. Retrieved from http://dx.doi.org/10.3390/app15105435
BibTeX	@article{Aydilek_2025, title={Improved War Strategy Optimization with Extreme Learning Machine for Health Data Classification}, volume={15}, ISSN={2076-3417}, url={http://dx.doi.org/10.3390/app15105435}, DOI={10.3390/app15105435}, number={10}, journal={Applied Sciences}, publisher={MDPI AG}, author={Aydilek, İbrahim Berkan and Uslu, Arzu and Kına, Cengiz}, year={2025}, month=may, pages={5435} }