文章摘要
REN Lei,YUE Chunfang,HE Xunjiang.RBF神经网络模型在金沟河流域径流预测中的应用Journal of Water Resources and Water Engineering[J].,2011,22(1):
RBF神经网络模型在金沟河流域径流预测中的应用
Application of RBF neural network model to the prediction of runoff in Jingouhe River Basin
  
DOI:10.11705/j.issn.1672-643X.2011.01.023
中文关键词: 径向基神经网络  归一化  MATLAB  径流预测  
英文关键词: radial basis of neural network  normalization  MATLAB  runoff forecast  
基金项目:教育部科学技术研究重点项目(209140); 新疆农业大学校前期资助课题; 新疆水利水电工程重点学科资助
Author NameAffiliation
REN Lei,YUE Chunfang,HE Xunjiang REN Lei1,YUE Chunfang1,HE Xunjiang2(1.College of Water Conservancy and Civil Engineering,Xinjiang Agricultural University,Urumqi 830052,China,2.Jingouhe River Basin Administration of Xinjiang,Shawan,Xinjiang 832100,China) 
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中文摘要:
      河川径流时间序列是一个复杂的非线性系统,使传统的预测方法难以描述其变化规律。将金沟河流域八家户站的1957年至2003年的年径流实测数据作为样本,转化为径流差后,进行归一化处理及自相关函数分析,在MATLAB环境下建立径向基神经网络径流预测模型。结果表明:与传统的BP神经网络预测比较,利用径向基神经网络模型对径流序列进行预测具有更高的精度和更短的运算时间,是径流预测的一种有效方法。
英文摘要:
      The traditional prediction methods are hard to describe the evolution rule of runoff which is a complicated non-linear time sequence system.Based on 1957-2003 annual runoff observed data in Bajiahu hydrological station in the Jingouhe River Basin,a runoff prediction model with RBF neural network was established in Matlab environment after the subtraction of the data was studied using normalization and autocorrelation algorithms.The results indicated that the prediction model with RBF neural network had high...
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