An Improved Golden Jackal Optimization Algorithm Using Opposition-Based Learning for Global Optimization and Engineering Problems
Abstract Golden Jackal Optimization (GJO) is a recently developed nature-inspired algorithm that is motivated by the collaborative hunting behaviours of the golden jackals in nature. However, the GJO has the disadvantage of poor exploitation ability and is easy to get stuck in an optimal local regio...
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| Główni autorzy: | , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Springer
2023-09-01
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| Seria: | International Journal of Computational Intelligence Systems |
| Hasła przedmiotowe: | |
| Dostęp online: | https://doi.org/10.1007/s44196-023-00320-8 |
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