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| New Optimized Method of High-Precision Grey GM(1,1) Forecasting Model |
| Shang Jun-liang; Fang Min |
| School of Computer Science & Technology, Xidian University, Xi’an 710071, China |
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Abstract 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 model’s grey derivative, regarding the value of x(1)(n) replacement of x(0)(1) as the model’s 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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Received: 22 May 2009
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Corresponding Authors:
Shang Jun-liang
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2010, Vol. 32 
