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首页> 外文会议>International Conference on Water and Environment(WE-2003); 20031215-18; Bhopal(IN) >Effect Of Noise In Parameter Estimation Of The Muskingum Model
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Effect Of Noise In Parameter Estimation Of The Muskingum Model

机译：噪声对Muskingum模型参数估计的影响

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摘要

The Muskingum model is commonly employed for the prediction of flood wave propagation. However, parameters of this model used for any reach are determined from the previous observations of inflows and outflows. The accuracy of the predicted outflow depends upon these observations which may have a significant amount of noise. The noise may be present in inflow or outflow only or in both inflow and outflow, or one may have noiseless data also. In this study, all these four cases are considered to investigate the effect of noise. Parameters of a linear Muskingum model are estimated by minimizing the sum of square of differences between observed and predicted outflows. Two methods, viz., Newton's method and Genetic Algorithm, are employed to estimate the parameters. Although a noise of zero mean is introduced in the inflow and outflow data, estimates of model parameters exhibit varying degrees of sensitivity in the analysis of noisy data.
机译：Muskingum模型通常用于预测洪水波传播。但是，用于该模型的参数可用于任何范围，这取决于先前对流入和流出的观察。预测流出量的准确性取决于这些观察结果，这些观察结果可能会产生大量噪声。噪声可能只存在于流入或流出中，也可能存在于流入和流出中，或者也可能具有无噪声的数据。在这项研究中，所有这四种情况都被认为是研究噪声的影响。线性Muskingum模型的参数是通过最小化观察到的流出量与预测流出量之差的平方和来估算的。采用两种方法，即牛顿法和遗传算法，来估计参数。尽管在流入和流出数据中引入了零均值噪声，但是模型参数的估计值在噪声数据分析中表现出不同程度的敏感性。

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