以x^((1))(n)为初始条件的GM模型

The GM Models that x^((1))(n) be Taken as Initial Value

自 1 98 2年灰色系统理论创立以来 ,关于GM模型的研究 ,都是以序列X(1 ) 的第一个分量作为灰色微分模型的初始条件进行建模的 ,这样造成对新信息利用不够充分。根据灰色系统理论的新信息优先原理 ,在建模过程中赋予新信息较大的权重可以提高灰色建模的功效。因此本文在建立灰色模型时 ,把X(1 ) 的第n个分量作为灰色微分模型的初始条件 ,对GM模型进行了改进 ,从而使所建模型的预测精度大为提高。最后 。

Since grey system theories were established by Prof.Deng,GM models and their improvement model all regarded the first vector of original sequence as the initialization,which resulted in deficiency using the latest information.Based on the principle in which new information should be used fully,we think it is a scientific way to pay more attention to the new information or endow them a more weight.So,this paper deals with the GM improvement in regarding the n-th vector as the initialization,and gets great improvement in forecasting precsision.Last,we validate the practicability and reliability of the models with examples.