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流域年均含沙量的B-P网络预测模型及其效果检验
引用本文:邓新民,李祚泳. 流域年均含沙量的B-P网络预测模型及其效果检验[J]. 成都信息工程学院学报, 1997, 0(2)
作者姓名:邓新民  李祚泳
作者单位:成都气象学院
摘    要:应用误差反向传播算法的人工神经网络,建立了流域年均含沙量的预测模型。该模型用于某流域年均含沙量预测的拟合率达90%以上,预留检验预报的准确率为75%。

关 键 词:人工神经网络;B-P算法;含沙量;预测

PREDICTION MODEL OF MEAN ANNUAL AMOUNT OF SEDIMENT IN A RIVER VALLEY USING B P NETWORKS
Deng Xinmin Li Zuoyong. PREDICTION MODEL OF MEAN ANNUAL AMOUNT OF SEDIMENT IN A RIVER VALLEY USING B P NETWORKS[J]. Journal of Chengdu University of Information Technology, 1997, 0(2)
Authors:Deng Xinmin Li Zuoyong
Affiliation:Chengdu Institute of Meteorology
Abstract:A prediction model for the amount of sediment in a river valley is presented using B P artificial neural networks.The model is applied to the prediction of the mean annual amount of sediment in a river valley.The results show that the fitting precision and prediction precision are 90% and 75%,respectively.
Keywords:Artificial neural network  B P algorithm  Amount of sediment  Prediction.  
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