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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| Главные авторы: | , , , , , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Springer
2026-02-01
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| Серии: | International Journal of Computational Intelligence Systems |
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1007/s44196-026-01169-3 |
| Метки: |
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