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Volume 32 Issue 6
Jun.  2010
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Shang Jun-liang, Fang Min. New Optimized Method of High-Precision Grey GM(1,1) Forecasting Model[J]. Journal of Electronics & Information Technology, 2010, 32(6): 1301-1305. doi: 10.3724/SP.J.1146.2009.00792
Citation: Shang Jun-liang, Fang Min. New Optimized Method of High-Precision Grey GM(1,1) Forecasting Model[J]. Journal of Electronics & Information Technology, 2010, 32(6): 1301-1305. doi: 10.3724/SP.J.1146.2009.00792

New Optimized Method of High-Precision Grey GM(1,1) Forecasting Model

doi: 10.3724/SP.J.1146.2009.00792
  • Received Date: 2009-05-22
  • Rev Recd Date: 2009-12-01
  • Publish Date: 2010-06-19
  • There are some problems in GM(1,1) model, such as, model method biased, compatibility condition not satisfied, transformation inconsistent and first number of the initial sequence not functioning high precision prediction in model after an accumulated generating operation. This paper deals with the GM(1,1) model improvement in reconstructing the GM(1,1) white background value, using white Background value weighted average of forward (backword) difference quotient as the new optimized models grey derivative, regarding the value of x(1)(n) replacement of x(0)(1) as the models initial condition. The new model improves the accuracy of the precision greatly. Even if the development coefficient is bigger than 2, the fitting precision of the new model is still high. The analysis of some examples indicates that the new optimized method using whether in low growth index series or in high growth index series has a very high practicability and reliability.
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