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Analysis and Prediction of Annual Runoff for Fen River Basin

机译:F河流域年径流量分析与预报

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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 mat: 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river河流域的径流特征。根据1960-2000年径流量数据,采用自相关分析方法确定模型输入变量,然后采用径向基函数人工神经网络识别前年径流量与后年径流量之间的关系。所开发的预测模型用于预测river河流域2001年至2015年的年径流量。结果表明:预测年径流量与观测年径流量相似,预测精度高。所开发的径向基函数人工神经网络模型可用于F河流域年径流量预报。研究成果对水资源的规划与管理具有重要意义。

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