Hybrid Learning–Driven Golden Jackal Optimizer for Reliable Parameter Estimation of Nonlinear Memristive Chaotic Systems
Abstract Accurate identification of parameters in chaotic and nonlinear systems is essential for ensuring precise modeling, control, and prediction of complex dynamical behaviors. However, conventional metaheuristic algorithms often struggle to maintain an effective balance between exploration and e...
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| Principais autores: | , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Springer
2026-02-01
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| Series: | International Journal of Computational Intelligence Systems |
| Assuntos: | |
| Acceso en liña: | https://doi.org/10.1007/s44196-026-01169-3 |
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