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A simple sensitivity analysis of the turbulence-induced flocculation model of cohesive sediment

机译:浊度沉积物湍流诱导絮凝模型的简单敏感性分析

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In this study, the local and global sensitivity analyses of the Winterwerp model to the input parameters have been carried out using the Garson algorithm and the PaD2 method by virtue of an artificial neural network. The main results of the sensitivity analyses are that the model is most sensitive to the breakup parameter and that only two parameters (the floc aggregation and breakup parameters) are significant. The result that the model output is less sensitive to the choice of fractal dimension seems to imply that the modification work on the fractal dimension might be unnecessary.
机译:在该研究中,通过人工神经网络利用Garson算法和PAD2方法来执行Winterwerp模型对输入参数的局部和全局敏感性分析。 灵敏度分析的主要结果是该模型对分析参数最敏感,并且只有两个参数(Floc聚合和分解参数)很大。 模型输出对分形尺寸的选择不太敏感的结果似乎暗示了分形维数的修改工作可能是不必要的。

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