
灰色模型GM(1,1)优化
罗党、刘思峰、党耀国
The Optimization of Grey Model GM (1,1)
Luo Dang、 Liu Sifeng、 Dang Yaoguo
分析了GM(1,1)模型产生模拟误差的原因,经大量的数据模拟和GM(1,1)模型比较,发现背景值的优化使GM(1,1)模型在短期、中期及长期预测中扩大了适用范围,并且模拟及预测精度显著提高。
This paper analyzes the reason that grey model GM (1,1) often makes errors in simulated data. By contrasting the optimum one to the GM (1,1) about the simulation, it can be concluded that the structure method of background value in grey model GM (1,1) has an important influence on the prediction and adaptability of the model. The optimum background value makes grey model GM (1,1) have better fitting and forecasting precision.
grey model GM (1 / 1) / winterization equation / background value
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