在灰色系统缓冲算子公理体系下，根据灰色系统的“新信息优先原理”，构造了一类调节强度可变的弱化缓冲算子，并对其特性进行了研究。针对不同的建模背景，通过调整缓冲算子的参数，可以生成具有不同弱化效果的序列。最后，利用本文提出的缓冲算子，对两个实际案例进行了建模计算，计算结果表明，这类新的弱化缓冲算子能够有效提高GM（1，1）模型的预测精度，解决定量预测结果与定性分析结论不符的问题。
Under the axiomatic system of buffer operator in grey system,a class of new weakening buffer operators whose adjustable intensity can be changed are constructed based on the ‘new information priority principle’ of grey system.The new weakening buffer operators are as following:x(k)d1=x(k)(x(n)/x(k))α,0 < α < 1,k=1,2,…,n. The new weakening buffer operators are very concise in the form, and are very convenient in the practical application.Then their characters are studied.In view of different modeling background,data sequences with different strengthening effect can be generated by adjusting the parameters of the buffer operator.Finally, the buffer operator that was put forward in this paper was used to the total energy consumption in Henan province in 2003-2009.The calculation results show that these new weakening buffer operators can effectively improve the forecasting accuracy of GM (1,1) model.This can solve the problem that the quantitative prediction results do not tally with the qualitative analysis.
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