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Research and Implementation of Quantum Evolution Algorithm Based on Immune Theory

机译:基于免疫理论的量子演化算法研究与实现

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The characteristics of quantum search algorithm and the mechanism of immune evolution are analyzed and discussed. Inspired by immune dynamic model and the mechanism in which immune cell can gradually accomplish affinity maturation during the self-evolution process, a quantum evolution algorithm based on immune operator is proposed. The algorithm can find out optimal solution by the mechanism in which antibody can achieve positive selection, memory cells can be produced, immune cell can accomplish cross-mutation, similar antibodies can be suppressed. It not only can maintain quite nicely the population diversity than the classical quantum evolution algorithm, but also can help to accelerate the convergence speed and converge to the global optimal solution rapidly. Some simulation experiments are shown to prove its superiority over other algorithms.
机译:分析和讨论量子搜索算法的特征及免疫演化机制。通过免疫动态模型的启发和免疫细胞在自进化过程中可以逐步完成亲和力成熟的机制,提出了一种基于免疫算子的量子演化算法。该算法可以通过抗体可以实现阳性选择的机制来发现最佳解决方案,可以制备存储器细胞,免疫细胞可以实现交叉突变,可以抑制类似的抗体。它不仅可以保持比古典量子演化算法的群体多样性,而且可以帮助快速加速收敛速度并汇聚到全局最佳解决方案。显示一些模拟实验证明其在其他算法上的优越性。

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