Boosted local dimensional mutation and all-dimensional neighborhood slime mould algorithm for feature selection
The slime mould algorithm (SMA) is a population-based optimization algorithm that mimics the foraging behavior of slime moulds with a simple structure and few hyperparameters. However, SMA has some limitations, such as getting trapped in local optima when dealing with multimodal or combinatorial fun...
- Autores:
-
Zhou, Xinsen
Chen, Yi
Wu, Zongda
Heidari, Ali Asghar
Chen, Huiling
Alabdulkreem, Eatedal
Escorcia-Gutierrez, José
Wang, Xianchuan
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2023
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/13556
- Acceso en línea:
- https://hdl.handle.net/11323/13556
https://repositorio.cuc.edu.co/
- Palabra clave:
- All-dimension neighborhood search
Classification
Feature selection
Local dimensional mutations
Meta-heuristic
Optimization
Slime mould algorithm
SMA
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)