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    改进的AEA算法及其在参数估计中的应用

    An Improved AEA Algorithm and Its Application to Parameter Estimation

    • 摘要: 提出一种基于AEA的改进算法——EAEA。该算法将分布估计算法和精英保留策略融入AEA算法中,用来产生AEA算法迭代需要的对比种群,使得算法能跳出局部最优,避免早熟现象的发生。在22个标准测试函数上进行实验,结果表明EAEA的寻优能力要好于其他算法。最后,将EAEA算法用于发酵动力学模型参数的估计,取得了良好的效果。

       

      Abstract: In this paper, an improved AEA algorithm, EAEA, is proposed, in which the estimation of distribution algorithm and elite reservation are integrated to generate a comparison population for iteration procedure so as to escape from local optimum and avoid prematurity effectively. It is shown from experimental results on 22 test functions that the EAEA can attain better search ability than some existing algorithms. Finally, the EAEA is also used in the parameter estimation of the kinetic models of fermentation.

       

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