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This simplified Matlab demo code shows how to use the new Mayfly Algorithm to solve clustering problems.
The only thing researchers need to do is to replace the data in "mydata.xlsx" with their data, and then run the MAclustering.m file in the Matlab platform.
Researchers are allowed to use this code in their research projects, as long as they cite as:
Mastrothanasis, K., Zervoudakis, K., Kladaki, M. & Tsafarakis, S. (2023). A bio-inspired computational classifier system for the evaluation of children’s theatrical anxiety at school. Education and Information Technologies. https://doi.org/10.1007/s10639-023-11645-4
and
Zervoudakis, K., & Tsafarakis, S. (2020). A mayfly optimization algorithm. Computers & Industrial Engineering, 145, 106559. https://doi.org/10.1016/j.cie.2020.106559
For more information go to: https://sites.google.com/view/kzervoudakis/research/metaheuristics/mayfly-algorithm
Citar como
Konstantinos Zervoudakis (2026). Clustering using Mayfly Optimization Algorithm (https://es.mathworks.com/matlabcentral/fileexchange/132777-clustering-using-mayfly-optimization-algorithm), MATLAB Central File Exchange. Recuperado .
Mastrothanasis, K., Zervoudakis, K., Kladaki, M. & Tsafarakis, S. (2023). A bio-inspired computational classifier system for the evaluation of children’s theatrical anxiety at school. Education and Information Technologies. https://doi.org/10.1007/s10639-023-11645-4
Zervoudakis, K., & Tsafarakis, S. (2020). A mayfly optimization algorithm. Computers & Industrial Engineering, 145, 106559. https://doi.org/10.1016/j.cie.2020.106559
Información general
- Versión 2.0.2 (20,8 KB)
Compatibilidad con la versión de MATLAB
- Compatible con cualquier versión
Compatibilidad con las plataformas
- Windows
- macOS
- Linux
