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《Urban Geotechnical Investigation & Surveying》 2008-01
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Research on a Residual Amendment Method of GM(1,1)Predictive Model Based on Neural Network

Guang Hui,Li GuoFen(Nanjing Forestry University,Nanjing 210037,China)  
With the shortcoming of GM(1,1)model predictive accuracy is low in a longer period,a new residual amendment method of GM(1,1)prediction model is put forward in this paper and the method based on neural network.Compared with the traditional residual GM(1,1)model correction method and verified by an engineering example,the method proposed in this paper can improve forecast accuracy effectively and extend forecast period and it has better application in engineering.
【CateGory Index】: TU196.1
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