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基于GIS的小波神经网络库区径流预报模型研究
引用本文:宋海良,宋洋,钟登华,钟炜.基于GIS的小波神经网络库区径流预报模型研究[J].水力发电学报,2008,27(1):5-10.
作者姓名:宋海良  宋洋  钟登华  钟炜
作者单位:天津大学建筑工程学院,天津,300072
摘    要:提出了一种基于GIS与小波神经网络方法相结合构建而成的水库日径流预测模型(GWNNR),通过模糊C均值聚类分析将水库历史径流数据分成4类,并分别建立相应的小波神经网络预测模型,应用遗传算法(Genetic algorithm)和误差反传递(Back-propagation)算法对模型的参数进行优化,对某水库2005年日平均来流进行分类预测,结果表明,该方法具有较好的训练速度和较高的预测精度.

关 键 词:工程管理  径流预测  小波神经网络  模糊C均值聚类  遗传算法  BP算法  小波神经网络  库区  日径流  预报模型  研究  wavelet  neural  networks  fuzzy  clustering  analysis  reservoir  runoff  forecasting  预测精度  训练速度  方法  结果  分类预测  来流  优化  参数  遗传算法  误差反传  Genetic
收稿时间:2007-09-12
修稿时间:2007年9月12日

Research on runoff forecasting of reservoir by using fuzzy clustering analysis and wavelet neural networks
SONG Hailiang,SONG Yang,ZHANG Denghua,ZHONG Wei.Research on runoff forecasting of reservoir by using fuzzy clustering analysis and wavelet neural networks[J].Journal of Hydroelectric Engineering,2008,27(1):5-10.
Authors:SONG Hailiang  SONG Yang  ZHANG Denghua  ZHONG Wei
Abstract:This paper presents a daily runoff forecasting method by using wavelet neural networks, the fuzzy Cmeans clustering analysis and the wavelet neural network. The historical runoff data are divided into four categories by using the fuzzy C-means clustering. The corresponding wavelet neural network is built, the parameters of model are optimized by genetic algorithm and the back-propagation algorithm. The daily mean runoff of reservoir in 2005 is forecasted under categories by the corresponding wavelet neural network. The forecasting result shows that the proposed method possesses the faster training speed and the greater forecasting accuracy.
Keywords:engineering management  runoff forecasting  wavelet neural networks  fuzzy C-means clustering  genetic algorithm  back-propagation algorithm
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