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- W2364283003 abstract "A multiple Baldwin effect based clonal selection algorithm(SAMBCSA) was proposed to improve the solution quality of classical clonal selection algorithm when dealing with complex multi-modal optimization problems.First,the ability of immune evolving was enhanced by the scheme of learning different information between different antibodies to find the promising solution regions.Second,an immune response strategy pool and a statistical self adaptive learning framework were designed in order to improve the universality of the algorithm.Then,the time complexity and the convergence of the algorithm were analyzed.The experimental results on 16 state-of-the-art benchmark functions indicated that,compared with clonal selection algorithm and some other algorithms,SAMBCSA achieves good performance with high solution quality and good robustness on most problems." @default.
- W2364283003 created "2016-06-24" @default.
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- W2364283003 date "2011-01-01" @default.
- W2364283003 modified "2023-09-25" @default.
- W2364283003 title "Self Adaptive Multiple Baldwin Effect Based Clonal Selection Algorithm" @default.
- W2364283003 hasPublicationYear "2011" @default.
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