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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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Kaydedildi:
Detaylı Bibliyografya
Yayımlandı:Comput Intell Neurosci
Asıl Yazarlar: Gao, Zheng-Ming, Zhao, Juan
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: Hindawi 2019
Konular:
Online Erişim: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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