文件名称:GM-code
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灰色系统理论将一切随机变化量看作是在一
定范围内变化的灰色量，将随机过程当作是在一定
范围、一定时区内变化的灰色过程，灰色预测[13,22]
是通过对原始数据进行累加生成或累减生成、级比
生成等，将杂乱无章的原始数据整理成规律性较强
的生成数据序列，再用微分拟合法建立微分方程来
描述生成数据序列的规律，最终通过对生成序列的
预测、还原来实现原始序列的预测-Grey system theory will all be seen as random variation in
Gray amount of variation within a given range, will be deemed to be in a certain stochastic process
Grey scope change process, certain time zone, gray prediction [13,22]
By the original data accumulated generating or regressive generation level than
Generation, the original data will be compiled into a chaotic strong regularity
The generated data sequence, and then fitting the establishment of differential equations to
Descr iption rule generation data sequence generated by the final sequence
Forecast, but also to achieve the original prediction of the original sequence
定范围内变化的灰色量，将随机过程当作是在一定
范围、一定时区内变化的灰色过程，灰色预测[13,22]
是通过对原始数据进行累加生成或累减生成、级比
生成等，将杂乱无章的原始数据整理成规律性较强
的生成数据序列，再用微分拟合法建立微分方程来
描述生成数据序列的规律，最终通过对生成序列的
预测、还原来实现原始序列的预测-Grey system theory will all be seen as random variation in
Gray amount of variation within a given range, will be deemed to be in a certain stochastic process
Grey scope change process, certain time zone, gray prediction [13,22]
By the original data accumulated generating or regressive generation level than
Generation, the original data will be compiled into a chaotic strong regularity
The generated data sequence, and then fitting the establishment of differential equations to
Descr iption rule generation data sequence generated by the final sequence
Forecast, but also to achieve the original prediction of the original sequence
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GM code.doc