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An Improved Grey Wolf Optimization Algorithm with Variable Weights
With a hypothesis that the social hierarchy of the grey wolves would be also followed in their searching positions, an improved grey wolf optimization (GWO) algorithm with variable weights (VW-GWO) is proposed. And to reduce the probability of being trapped in local optima, a new governing equation...
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| Publicado en: | Comput Intell Neurosci |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Hindawi
2019
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6589244/ https://ncbi.nlm.nih.gov/pubmed/31281334 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2019/2981282 |
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