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首页> 外文期刊>Arabian journal of geosciences >Estimating width of the stable channels using multivariable mathematical models
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Estimating width of the stable channels using multivariable mathematical models

机译:使用多变量数学模型估算稳定通道的宽度

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摘要

Predicting behavior and the geometry of the channels and alluvial rivers in which the erosion and sediment transport are in equilibrium is one of the most important topics in river engineering. Various researchers have proposed empirical equations to estimate stable river width (W). In this research, empirical equations were examined and tested with a comprehensive available data set consisting of 1644 points collected from 29 stable rivers in various parts of the world. The data set covers a wide range of flow conditions, river geometry, and bed sediments. This data set is classified in two groups (W < 600 m and W >= 600 m) for presenting the new models. The new linear and nonlinear multivariable equations were fitted to these two groups, and the best models were selected by preliminary tests and diagnostic determined for each group. The determination coefficient of these models ranged from 0.87 to 0.96. The results show that the models presented in this paper are more accurate with respect to the previously presented models. In the second part, "Artificial neural networks," perceptron was used and a new methodology for estimating stable channel width was developed. Comparison of the statistical methods presented in this paper and the results of perceptron neural network revealed preferential recent method.
机译:预测侵蚀和泥沙输送处于平衡状态的河道和冲积河流的行为和几何形状是河流工程中最重要的主题之一。许多研究人员提出了经验方程来估算稳定的河宽(W)。在这项研究中,对经验方程进行了检验和测试,并获得了全面的可用数据集,该数据集由从世界各地29条稳定河流中收集的1644个点组成。数据集涵盖了广泛的流量条件,河流几何形状和河床沉积物。该数据集分为两类(W <600 m和W> = 600 m),以展示新模型。将新的线性和非线性多变量方程拟合到这两组,并通过初步测试选择最佳模型,并为每组确定诊断。这些模型的确定系数范围为0.87至0.96。结果表明,本文提出的模型相对于先前提出的模型更为准确。在第二部分“人工神经网络”中,使用了感知器,并开发了一种估计稳定通道宽度的新方法。通过比较本文提供的统计方法和感知器神经网络的结果,我们发现了优先使用的最新方法。

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