Polar Lights Optimizer: Algorithm and Applications
Version 1.0.1 (3,14 Mo) par
Ali Asghar Heidari
Polar Lights Optimizer: Algorithm and Applications in Image Segmentation and Feature Selection
This study introduces Polar Lights Optimization (PLO), a metaheuristic algorithm inspired by the aurora phenomenon or polar lights. The aurora is a unique natural spectacle that occurs when energetic particles from the solar wind converge at the Earth's poles, influenced by the geomagnetic field and the Earth's atmosphere. By analyzing the motion of high-energy particles and delving into the underlying principles of physics, we propose a unique model for mimicking particle motion. This model integrates both gyration motion and aurora oval walk, with the former facilitating local exploitation while the latter enabling global exploration. By synergistically combining these two strategies, PLO achieves a better balance between local exploitation and global exploration. Additionally, a particle collision strategy is introduced to enhance the efficiency of escaping local optima. To evaluate the performance of PLO, a qualitative analysis experiment is designed to assess its ability to explore the problem space and search for solutions. PLO is compared with nine classic algorithms and eight high-performance algorithms using 30 benchmark functions from IEEE CEC2014. Furthermore, we compare and analyze PLO with the current state-of-the-art methods in the field, utilizing 12 benchmark functions from IEEE CEC2022. Subsequently, PLO is successfully applied to multi-threshold image segmentation and feature selection. Specifically, a PLO-based multi-threshold segmentation model and a binary PLO-based feature selection method are developed. The performance of PLO is also evaluated using 10 images from the Invasive Ductal Carcinoma (IDC) medical dataset, while the overall adaptability and accuracy of the feature selection model are tested using 8 medical datasets. These results affirm the emergence of PLO as an effective optimization tool ready for solving real-world problems, including those in the medical field. The source codes of PLO are available in https://aliasgharheidari.com/PLO.html
Citation pour cette source
Yuan, Chong, et al. “Polar Lights Optimizer: Algorithm and Applications in Image Segmentation and Feature Selection.” Neurocomputing, Elsevier BV, Aug. 2024, p. 128427, doi:10.1016/j.neucom.2024.128427.
Compatibilité avec les versions de MATLAB
Créé avec
R2024a
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS LinuxTags
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
Moss Growth Optimization (MGO)-2024
Parrot Optimizer (PO)-2024
Polar Lights Optimizer (PLO)-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 | |
---|---|---|---|
1.0.1 | 2024 |
||
1.0.0 |