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- W2388898830 abstract "As the traditional adaptive dynamic clone selection algorithm has some shortcomings,such as slow convergence,low accuracy and low population diversity,a new clone selection algorithm for searching optimal solution of function is studied and an adaptive dynamic clone selection algorithm is presented to improve it,which is based on sphere crossover.Firstly,using floating-point encoding,the mutation probability of each antibody is dynamically calculated in each iteration process,according to antibody affinity.And then,according to the size of antibody affinity,antibody populations are dynamically divided into memory antibody units and general antibody units.Subsequently,antibody populations are adjusted by sphere crossover so that algorithm convergence speed and solution accuracy are improved.The effectiveness and the feasibility of the proposed algorithm are verified by examples." @default.
- W2388898830 created "2016-06-24" @default.
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- W2388898830 date "2010-01-01" @default.
- W2388898830 modified "2023-09-26" @default.
- W2388898830 title "Adaptive Dynamic Clone Selection Algorithm Based on Sphere Crossover" @default.
- W2388898830 hasPublicationYear "2010" @default.
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