基于自适应小波神经网络的数据挖掘方法研究——对我国石油产量的预测分析
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财经研究 2006 年 第 32 卷第 03 期, 页码：116 - 122
摘要
参考文献
摘要
小波神经网络是近年来在小波分析研究获得突破性进展基础上提出的一种前馈型网络,文章将小波与神经网络相结合,提出了一种基于自适应小波神经网络(SAWNN,self-adaptation wavelet neural network)的数据挖掘方法,并构造了数据挖掘过程的机器学习机制,以提高对问题的处理能力。文章将所构造的自适应小波神经网络用于石油产量的建模预测研究,实证结果表明此预测模型不仅是有效的,而且是可行的。
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①数据来源中国统计局信息中心。
[2]Yongyong He,Fulei Chu,Binglin Zhong.A hierarchical evolutionary algorithm for con-structing and training wavelet networks[J].Neural Comput&Applic,2002,10:336~357.
[3]Chris C Holmes,Bani K.Mallick,bayesian wavelet networks for nonparametric regres-sion[J].IEEE Trans.On Neural Networks,2000,11(1):27~35.
[4]Jun Zhang,Gilbert G Walter,Yubo Miao,Wan Ngai Wayne Lee.Wavelet neural net-works for function learning[J].IEEE Trans.Signal Processing,1995,43(6):1485~1496.
[5]Y C Huang.Fault identification of power transformers using genetic-based wavelet net-works[J].IEE Proc-Sci.Meas.Technol,2003,150(1):25~30.
[6]Wei-ming Wang,Chao-ming Huang.An evolutionary based wavelet network for real-time power dispatch[J].Electric Power Components and Systems,2002,(30):1151~1166.
[7]Takashi Samatsu,Eiji Uchino,Takeshi Yamakawa.Feature extraction of a vectorcar-diogram by employing a wavelet network guaranteeing a global minimum[J].Journal ofIntelligent and Fuzzy Systems,2000,(8):221~227.
[8]G P Liu S A,Billings V,Kadirkamanathan.Nonlinear system identification using wave-let networks[J].International Journal of Systems Science,2000,3(12):1531~1542.
[9]Leonardo M Reyneri.Unification of neural and wavelet networks and fuzzy systems,IEEE trans[J].On Neural Networks,1999,10(4):801~814.
[10]Stephen A Billings,Hua-Liang Wei.A new class of wavelet networks for nonlinearsystem identification,IEEE Trans[J].On Neural Networks,2005,16(4):862~874.
①数据来源中国统计局信息中心。
引用本文
刘兰娟, 谢美萍. 基于自适应小波神经网络的数据挖掘方法研究——对我国石油产量的预测分析[J]. 财经研究, 2006, 32(3): 116–122.
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