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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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Detalles Bibliográficos
Autores principales:	Zhang, Ruirui, Li, Tao, Xiao, Xin, Shi, Yuanquan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Hindawi Publishing Corporation 2013
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3590445/ https://www.ncbi.nlm.nih.gov/pubmed/23483853 http://dx.doi.org/10.1155/2013/810320

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