Research on Immune Algorithm of Subregional Caccine Extraction

An Quan Jiao; Xiao Ling Li; Sheng Zhong

doi:10.4028/www.scientific.net/AMM.263-266.2155

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Particle Swarm Optimization Based on Multiobjective Optimization
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 263-266Research on Immune Algorithm of Subregional...

Research on Immune Algorithm of Subregional Caccine Extraction

Abstract:

Based on the analysis of the flaw mechanism of tradition genetic algorithm and critically inheriting the immunity theory foundation, the paper proposes a new optimized algorithm - Subregion Artificial immunity Optimized Algorithm Based on Parallel, which can speed up the partially convergence and at the same time maintain the global convergence through the simulation of actual immunity behavior of organism. The basic thought of this algorithm is firstly to divide a complex question into several simple questions, secondly to carry out parallel “immunity” computation according to those simple questions, thirdly to pour the results (the antibodies) into the global immunity algorithm, which not only simplifies the complex question, but also raises the efficiency of the algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 263-266)

Pages:

2155-2159

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.263-266.2155

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Online since:

December 2012

Authors:

An Quan Jiao*, Xiao Ling Li, Sheng Zhong

Keywords:

Immune Algorithm, Immune Vaccine, Subregional

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