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The BP neural network model and application based on genetic algorithm

机译:基于遗传算法的BP神经网络模型及其应用

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In order to deal with the defects of the poor convergences and easily immerging in partial minimum frequently, a new algorithm is proposed based on the combination of genetic algorithm and BP neural network, which is called GA- BP algorithm. This algorithm is applied to optimization of initial weights of BP Network, the structure and learn rule. It searches through the total solution space and can find the optimal solution globally over a domain. In this paper, GA- BP algorithm is applied to the production practice of molecular distillation to purify essential oils in schisandra chinensis. The result shows that this algorithm greatly increases convergent speed and convergence accuracy comparing with the simplex BP algorithm, and could achieve better results.
机译:为了解决收敛性差,容易频繁陷入局部极小的缺点,提出了一种基于遗传算法和BP神经网络相结合的算法GA-BP。该算法适用于BP网络初始权重,结构和学习规则的优化。它搜索整个解决方案空间,并可以在一个域中全局找到最佳解决方案。本文将GA-BP算法应用于分子蒸馏的生产实践中,以纯化五味子中的香精油。结果表明,与单纯形BP算法相比,该算法大大提高了收敛速度和收敛精度,取得了较好的效果。

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