A Danger-Theory-Based Immune Network Optimization Algorithm

Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generate...

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Detaylı Bibliyografya
Asıl Yazarlar: Zhang, Ruirui, Li, Tao, Xiao, Xin, Shi, Yuanquan
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: Hindawi Publishing Corporation 2013
Konular:
Research Article
Online Erişim:https://ncbi.nlm.nih.gov/pmc/articles/PMC3590445/
https://ncbi.nlm.nih.gov/pubmed/23483853
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2013/810320
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