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...

Descripción completa

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

Internet

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

Ejemplares similares