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A stepwise-cluster forecasting approach for monthly streamflows based onn climate teleconnections

机译:基于气候远程连接的月流量分步聚类预测方法

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摘要

In this study, a stepwise cluster forecasting (SCF) framework is proposed for monthly streamflow prediction in Xiangxi River, China. The developed SCF method can capture discrete and nonlinear relationships between explanatory and response variables. Cluster trees are generated through the SCF method to reflect complex relationships between independent (i.e. explanatory) and dependent (i.e. response) variables in the hydrologic system without determining specific linearonlinear functions. The
机译:在这项研究中,提出了一种逐步聚类预测(SCF)框架,用于中国湘西河的月流量预测。开发的SCF方法可以捕获解释变量和响应变量之间的离散和非线性关系。通过SCF方法生成聚类树,以反映水文系统中独立变量(即解释性变量)和因变量(即响应性变量)之间的复杂关系,而无需确定特定的线性/非线性函数。的

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