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中文摘要：
本文提出了一种结合文化算法的AEA算法，它利用文化算法中的信度空间来保存种群中的优质个体，然后通过影响函数来生成新种群。改进的AEA算法能够快速收敛到全局最优值，对典型函数的测试和工业模型参数估计的应用表明：改进的算法全局搜索能力和收敛速度比原始的AEA算法有所提高。
英文摘要：
In the paper,we proposed an AEA combined with cultural algorithm. It uses reliability space of cultural algorithm to save the elite particles of the swarm, and then generate the new population through the influence function.The improved AEA can quickly converge to the global optimal of the typical functions. The results of testing example functions and modeling industry based on neural network show that the global search ability and the convergence rate of the modified algorithm are improved.
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