| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560705 |
| ISSN: | 1405-5546 |
| Autores: | Kawano, Yunkio1 Valdez, Fevrier1 Castillo, Óscar1 |
| Instituciones: | 1Tijuana Institute of Technology, Computer Science Department, México |
| Año: | 2022 |
| Periodo: | Abr-Jun |
| Volumen: | 26 |
| Número: | 2 |
| Paginación: | 743-757 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | In general, this paper is focused on creating a fuzzy combination of two optimization algorithms. In this case, the algorithms work with populations and allow us to migrate between them every certain number of iterations. On the other hand, fuzzy logic is responsible for the dynamic adjustment of parameters within each of the algorithms since the variables are different in each algorithm. In previous works, a combination between genetic algorithm and particle swarm optimization was developed, which motivated us to create this combination expecting to obtain better results when compared to the previous works. The moth-flame optimization and lightning search algorithm were combined to obtain a powerful hybrid metaheuristic combining the advantages of both individual algorithms. |
| Disciplinas: | Ciencias de la computación, Ciencias de la computación |
| Palabras clave: | Inteligencia artificial, Procesamiento de datos |
| Keyword: | Artificial intelligence, Data processing |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
