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水力发电学报 ›› 2023, Vol. 42 ›› Issue (5): 1-9.doi: 10.11660/slfdxb.20230501

• •    下一篇

编辑部推荐论文:河流阻力特征参量提取及SVM辅助河床形态判识

  

  • 出版日期:2023-05-25 发布日期:2023-05-25

Extraction of flow resistance characteristic parameters and SVM-assisted riverbed morphology identification

  • Online:2023-05-25 Published:2023-05-25

摘要: 床面形态的变化影响着泥沙输移和水流阻力,是河床演变的重要方面。预测床面形态变化对河道整治和泥沙研究具有实际意义。本文基于水流阻力规律确定了判别床面形态的特征参数;通过对特征参数与床面形态关系的分析,发现特征参数与床面的形态的关系呈“S”型;利用决策向量机(SVM)多分类法对床面形态进行自动划分,根据划分结果对无量纲特征参数进行非线性和线性拟合,得到拟合函数;对特征参数与沙波形态的拟合函数进行求导分析,计算得出河床在各沙波形态下的特征参数取值范围,确定河床形态判别标准;结合试验数据和实测资料对河床形态判别标准进行验证,结果表明本文所述方法在河床形态识别方面具有可行性和准确性。

关键词: 河流动力学, 河床形态, 阻力规律, SVM多分类, 河床形态参数

Abstract: Sediment transport and flow resistance are affected by riverbed morphology. As an important aspect of riverbed evolution, effective predictions of bed form changes are practically significant for river regulation and sediment research. This paper determines the characteristic parameters of riverbed forms based on the law of flow resistance. We find an ‘S’-shaped relationship exists between the characteristic parameters of the flow and bed form through analysis of previous experimental data. By automatic division of the bed forms using a SVM multi-classification method, we obtain a fitting function from the nonlinear and linear fittings of dimensionless characteristic parameters, and determine the criterion of riverbed forms through a derivative analysis of the fitting function of characteristic parameters and the sand wave forms. Finally, this criterion is verified against the previous laboratory experimental data and in-situ measurements in literature, showing the method is feasible and quite accurate in riverbed shape recognition.

Key words: river dynamics, riverbed form, resistance law, SVM, morphological parameters

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