Forecasting Approach for Different Scales of Runoff Based on the Wavelet Analysis and Neural Network
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摘要: 本文探讨了小波神经网络在径流预测中的应用。该方法结合了神经网络和小波转化的优点，弥补了人工神经网络在预测应用中的不足，较好的追踪预测径流时间序列中的突变性，强转折性，奇异性点等。并且本研究通过与人工神经网络预测方法比较研究，得出小波神经网络能取得更高精度的不同尺度的径流预测值。
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关键词:
- 径流预测
Abstract: This pape discussed the application of the wavelet analysis and neural network method in runoff predicted. This method unified the merits of which are the neural networks and the wavelet transform . The wavelet analysis and neural network method made up the defective of Artifical Neural Network in forecast application. And this method can well trace forecast the special points which have some characteristic, sudden change ,strong sinuous and irregularity, in runoff time series. Comparison was made between the wavelet analysis and neural network method with artificial neural network. The comparison result indicated the wavelet analysis and neural network method obtained the high accuracy runoff predicted value.-
Keywords:
- runoff forecasting
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[10]杨琦, 张建华, 王向峰, 等.基于小波-神经网络的风速及风力发电量预测[J].电网技术,2009,33(17):44-48
[1]Dwight F M.[J].Kraig J. Olejniczak. Elements of wavelets for engineers and scientist[M]. New York: John Wiley & Sons, Inc,2003,:-
[2]侯木舟, 袁修贵.基于MATLAB的小波分析在股市技术分析中的应用[J].系统工程,2001,19(5):86-91
[3]牛东晓, 邢棉.时间序列的小波神经网络预测模型的研究[J].系统工程理论与实践,1999,5:89-92
[4]Kreinovich V, Sirisaengtaksin O, Cabren S.Wavlet neural networks are asymptotically optimal approximates for function of ne variable[C][J].Proceeding of IEEE 1994 Int’1 Conf Neural Networks (1), Florida, USA,1994,1:299-304
[5]曹洪民, 张玉林, 姜永鹏, 等.基于小波神经网络的煤矿瓦斯涌出量预测[J].计算机应用与软件,2009,26(7):168-170
[6]陈昌彦, 王思敬, 沈小克.边坡岩体稳定性的人工神经网络预测模型[J].岩土工程学报,2001,23(2):157-161
[7]张少文, 张学成, 王玲, 等.黄河年降雨-径流Bp预测模型研究[J].人民黄河,2005,27(1):18-20
[8]蓝永超, 康尔泗, 徐中民, 等.Bp神经网络在径流长期预测中的应用[J].中国沙漠,2001,21(1):97-100
[9]蔡煜东, 姚林声.径流长期预报的人工神经网络方法[J].水科学进展,1995,6(1):61-65
[10]杨琦, 张建华, 王向峰, 等.基于小波-神经网络的风速及风力发电量预测[J].电网技术,2009,33(17):44-48
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