首页> 外文期刊>Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group >Developing an expert group method of data handling system for predicting the geometry of a stable channel with a gravel bed
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Developing an expert group method of data handling system for predicting the geometry of a stable channel with a gravel bed

机译:开发数据处理系统的专家组方法,以预测砾石床的稳定通道几何形状

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Predicting the geometry of channels and alluvial rivers is of primary importance in river engineering science. Appropriately designing channels and predicting stable river cross-sections can decrease costs and prevent the destruction of installations and agricultural land by rivers. Consequently, researchers have applied different empirical and regression methods to achieve relations for predicting stable channel and river geometry. In this study, Group Method of Data Handling] GMDH) models are used to predict three geometric variables of stable channels, namely width (w), depth (h) and slope (s). The effect of different input parameters, such discharge (Q), median grain size (d(50)) and the Shields parameter (tau*) on the GMDH models is assessed with regard to predicting stable channel geometry. The results indicate that the GMDH model with mean absolute percentage error (MAPE) of 5.53%, 4.05% and 4.89% for channel width, depth and slope prediction respectively, exhibits good accuracy. Moreover, a comparison of the GMDH models with previous theoretical equations (based on regression analysis) indicates the superiority of GMDH model performance, with error reductions of one-fifth, one-eighth and one-sixth compared with the regression equations for channel width, depth and slope prediction, respectively. Copyright (C) 2016 John Wiley & Sons, Ltd.
机译:预测渠道的几何形状和冲积河流在河流工程科学中具有重要意义。适当地设计渠道和预测稳定的河流横截面可以降低成本并防止河流破坏安装和农业土地。因此,研究人员应用了不同的实证和回归方法来实现预测稳定通道和河流几何的关系。在本研究中,数据处理的组方法] GMDH)模型用于预测稳定通道的三个几何变量,即宽度(W),深度(H)和斜率。在预测稳定的通道几何形状,评估不同输入参数,这种放电(Q),中值粒度(D(50))和屏蔽参数(TAU *)的效果。结果表明,对于通道宽度,深度和斜坡预测,具有5.53%,4.05%和4.89%的平均绝对百分比误差(MAPE)的GMDH模型表现出良好的准确性。此外,与先前的理论方程式(基于回归分析)的GMDH模型的比较表明了GMDH模型性能的优势,而误差减少了第五个,第五个,第一个和第六次,与信道宽度的回归方程相比,分别深度和斜坡预测。版权所有(c)2016 John Wiley&Sons,Ltd。

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