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。
Markov Chain is suitable for short-term forecast of great capacity sample data sequence, but gray system forecast method is suitable for medium-term forecast of few capacity sample data sequence.
马尔柯夫链适用于大样本数据序列的短期预测，而灰色系统预测方法适用于小样本数据的中期预测。
By using the grey model to simulate and forecast the above sequence data, and through forecasting a certain regional yeild by the anti-formula that pushed the commercial real estate market value.
本文利用灰色系统模型所得数据序列进行模拟与预测，进而通过对某一区域的收益还原率进行预测并由反推公式得出该商业地产的市场价值。
By using the grey model to simulate and forecast the above sequence data, and through forecasting a certain regional yeild by the anti-formula that pushed the commercial real estate market value.
本文利用灰色系统模型所得数据序列进行模拟与预测，进而通过对某一区域的收益还原率进行预测并由反推公式得出该商业地产的市场价值。
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