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Analysis and Prediction of Annual Runoff for Fen River Basin

机译:汾河流域年径流分析与预测

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The runoff characteristics of Fen river basin was analyzed first. According to the runoff data of 1960-2000, autocorrelation analysis method was used to determine model input variables and then radial basis function artificial neural network was used to recognize the relationship between previous annual runoff and later annual runoff. The developed prediction model was used to predict the annual runoff of 2001 to 2015 of Fen river basin. The result shows that: the predicted annual runoff was similar to the observed annual runoff, which means high prediction accuracy; the developed radial basis function artificial neural network model can be used for annual runoff prediction of Fen river basin. The research results are of great importance for water resource planning and management.
机译:首先分析了汾河流域的径流特征。根据1960 - 2000年的径流数据,使用自相关分析方法来确定模型输入变量,然后使用径向基函数人工神经网络来识别以前的年度径流和后来的年度径流之间的关系。发达的预测模型用于预测2001年至2015年汾河流域的年度径流。结果表明:预测的年度径流类似于观察到的年径流,这意味着高预测准确性;发达的径向基函数人工神经网络模型可用于汾河流域的年径流预测。研究结果对于水资源规划和管理具有重要意义。

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