In accordance with analysis of various examples, this paper points out that so far as same primitive sequence is concerned, forecasting value of GM(1,1) enlarges when the calculating null point rises, and the second term of the new sequence decreases, and cumulative number increases.
根据各种应用实例的分析，指出对于同一原始序列来说，当计算零点升高、新序列的第二项减小或累加次数增多时，ＧＭ（１，１）模型的预测值增大，同时指出这些问题是由ＧＭ（１，１）模型本身的特点所决定的。
So in this paper,an improved gray forecasting model was proposed based on the basic principles of grey model which use one-accumulated exponential model.
灰色预测模型要求原始数据序列满足指数规律,而实际上城市用水波动性大,无典型指数趋势变化,而一般呈代数曲线形式变化,因此本文提出了改进的灰色模型在城市年用水量预测中的应用,改进的灰色预测模型主要基于灰色预测模型一次累加的建模思路。
s one-accumulate living water quantity time-series data have the obvious line trend; The industry water quantity time-series data obey one kind of variety polynomial.
在对某市年用水量随机时间序列原始数据进行预处理的基础上,发现年生活用水量的一次累加时间序列数据具有明显的线性趋势。
Because of the city s annual water consumption forecasting time-series has the characteristics of randomness,and one-accumulate methods has the characteristics of smoothing time-series randomness,improving rule ness and it s easy for regressing.
基于年需水量原始时间序列具有非线性随机变化的特点,而一次累加法具有削弱时间序列随机性、增加时间序列规律性、便于回归函数拟合的特点,该文提出了一次累加回归分析法在城市年需水量预测中的应用。