non-smooth degree 不平滑度
surface smooth degree 表面平整度
Sequence Smooth Degree 序列光滑度
smooth degree of layer 面层平整度
The primary research content and results are obtained as followes:1. The smooth degree of modeling data series is one of the important factors that impact forecasting precision of grey model.
本文在平移变换和伸缩变换的基础上提出了含参线性函数变换改进的灰色预测模型,证明了含参线性函数变换能提高建模数据序列的光滑度,给出了数值算例,并分析了改进模型的拟合精度和预测效果。
参考来源 - 灰色预测模型的改进及其应用·2,447,543篇论文数据，部分数据来源于NoteExpress
Its fitting precision is related to the smooth degree of modeling data sequence.
它的拟合精度与建模数据序列的光滑度有关。
The accuracy of grey forecasting model (GM) is increased by improving the smooth degree of original data sequence.
用提高原始数据列光滑度的方法来提高灰色预测模型(GM模型)的精度。
This paper proves that the smooth degree of a data row can be increased by transforming the counter-hyperbolic sine function.
证明了利用反双曲正弦函数变换能提高数据列的光滑程度，给出了改善的自回归预测方法，并且举例加以论证。
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