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On the Essential Conditions of Difference Information and Class Ratio Dispersion of Several Kinds of Data Processing Methods Reducing in Grey Predicting Modelling

机译:灰色预测建模中减少的几种数据处理方法的差异信息和类比色散的必要条件

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摘要

In this paper, author presents the essential conditions of difference information and class ratio dispersion reducing by logarithm and root sequence. They also point out that although new data is in the range suitable of the model, the error after it returns to original state might be great.
机译:在本文中,作者提出了差异信息和类比离散度通过对数和根序列减少的基本条件。他们还指出,尽管新数据在该模型的适用范围内,但返回原始状态后的误差可能很大。

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