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ASSESSMENT OF LONGITUDINAL DISPERSION COEFFICIENT BY MEANS OF DIFFERENT NEURAL NETWORKS

机译:不同神经网络对纵向色散系数的评估

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摘要

Multi-Layer Perceptron, Fuzzy and Radial-Basis Function neural networks, Nearest Neighbour approach, linear regression, 2~(nd) order curvilinear regression, and 'classical' empirical formulae have been applied for evaluation of longitudinal dispersion coefficient for a river reach. In general, results achieved by means of each type of neural networks outperforms these obtained by other techniques.
机译:多层感知器,模糊和径向基函数神经网络,最近邻方法,线性回归,二阶(二阶)曲线回归和“经典”经验公式已用于评估河道的纵向弥散系数。通常,通过每种类型的神经网络获得的结果都优于通过其他技术获得的结果。

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