Parrot optimizer: Algorithm & application to medical problem
Version 1.0.7 (2,98 Mo) par
Ali Asghar Heidari
This paper introduces the Parrot Optimizer (PO), an efficient optimization method
Stochastic optimization methods have gained significant prominence as effective techniques in contemporary research, addressing complex optimization challenges efficiently. This paper introduces the Parrot Optimizer (PO), an efficient optimization method inspired by key behaviors observed in trained Pyrrhura Molinae parrots. The study features qualitative analysis and comprehensive experiments to showcase the distinct characteristics of the Parrot Optimizer in handling various optimization problems. Performance evaluation involves benchmarking the proposed PO on 35 functions, encompassing classical cases and problems from the IEEE CEC 2022 test sets, and comparing it with eight popular algorithms. The results vividly highlight the competitive advantages of the PO in terms of its exploratory and exploitative traits. Furthermore, parameter sensitivity experiments explore the adaptability of the proposed PO under varying configurations. The developed PO demonstrates effectiveness and superiority when applied to engineering design problems. To further extend the assessment to real-world applications, we included the application of PO to disease diagnosis and medical image segmentation problems, which are highly relevant and significant in the medical field. In conclusion, the findings substantiate that the PO is a promising and competitive algorithm, surpassing some existing algorithms in the literature. The supplementary files and open-source codes of the proposed parrot optimizer (PO) is available at https://aliasgharheidari.com/PO.html.
Citation pour cette source
Lian, Junbo, et al. “Parrot Optimizer: Algorithm and Applications to Medical Problems.” Computers in Biology and Medicine, Elsevier BV, Feb. 2024, p. 108064, doi:10.1016/j.compbiomed.2024.108064.
Compatibilité avec les versions de MATLAB
Créé avec
R2023b
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS LinuxTags
Remerciements
A inspiré : An Efficient Improved Parrot Optimizer
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Découvrir Live Editor
Créez des scripts avec du code, des résultats et du texte formaté dans un même document exécutable.
Artemisinin Optimizer (AO)-2024
Educational Competition Optimizer (ECO)-2024
Fata Morgana Algorithm (FATA)-2024
Harris Hawk Optimization (HHO)-2019
Hunger Games Search (HGS)-2021
Parrot Optimizer (PO)-2024
Rime Optimization Algorithm (RIME)-2023/RIME Iteration version
Rime Optimization Algorithm (RIME)-2023/RIME function evaluation version
Runge Kutta Optimization (RUN)-2021
Slime mould algorithm (SMA)-2020
Weighted Mean of Vectors (INFO)-2022
Version | Publié le | Notes de version | |
---|---|---|---|
1.0.7 | . |
||
1.0.6 | Version 2 in 10 April 2024 uploaded- run bugs fixed |
||
1.0.5 | p |
||
1.0.4 | doi |
||
1.0.3 | public version |
||
1.0.2 | 1 |
||
1.0.1 | version 1 |
||
1.0.0 |