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《Journal of Anhui University of Technology and Science(Natural Science)》 2007-01
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Research of RBF neural network prediction method based on PCA

WU Chang-rong1,YE Ming-Quan2,HU Xue-gang3(1.Coll.of Math.& Comp.Sci.,Anhui Normal University,Wuhu 241000,China;2.Comp.Staff Room,WanNan Medical College,WuHu 241000,China;3.Inst.of Comp.& Info.,Hefei University of Technology,Hehei,230009,China)  
Principal Component Analysis(PCA) method can produce optimal compression of samples and reduce dimensions of samples.In general,a RBF neural network is used to predict multi-variable time sequence,in which the number of sample's characteristic variables is too large to deal with.An improved method has been developed by PCA to process original data.Some principal components are selected as the input nodes of the neural network.The experiment and simulation show that the model of RBF neural network based on PCA has better effect than the common RBF neural network model,the construction of RBF network is simplified,and the precision is increased.
【Fund】: 安徽省教育厅自然科学基金资助项目(2005kj094);; 安徽师范大学专项基金资助项目(2005bzx19)
【CateGory Index】: TP183
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