For problems to forecast sequence, it is important and effective to use data directly and not change them artificially in order to mine true rules of the object.
对序列问题的预测，提出处理的方法应尊重数据本身规律，不人为的采取另行预处理，以便能挖掘出对象的本质规律。
The GM (1, 1) forecast model fits in with mainly the smooth data sequence.
灰色预测模型GM(1,1)主要适用于光滑数据序列的预测。
This paper presents the residual error forecast model of average-growing function by using its residual error data sequence to adjust the model based on the finished forecast model.
在均生函预报模型的基础上，利用其残差数据序列对均生函数预报模型进行校正，提出了均生函数残差预报模型。
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