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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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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Hindawi Publishing Corporation
2013
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| Assuntos: | |
| Acesso em linha: | 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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