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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...
Autores principales: | Gao, Zheng-Ming, Zhao, Juan |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589244/ https://www.ncbi.nlm.nih.gov/pubmed/31281334 http://dx.doi.org/10.1155/2019/2981282 |
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