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Grey New Information GOM(1,1) Model and its Application Based on Opposite-direction Accumulated Generating and Background Value Optimization

机译:灰色新信息GOM(1,1)模型及其基于对立方向累计生成和背景值优化的应用

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The accuracy of the traditional grey model is not high for the monotonic decreasing data. The paper uses the opposite-direction accumulated method and makes full use of new information combined with optimization of the background values. It induces the formula of the parameters in the model and establishes the grey new information GOM(1,1) model in which it is based on the opposite-direction accumulated operation and optimization of the background values. It is a new method of the grey model. The examples show it is with higher accuracy than that of non-new information model.
机译:对于单调减少数据,传统灰色模型的准确性不高。本文采用相反方向累积的方法,充分利用新信息与背景值的优化相结合。它引起了模型中的参数的公式,并建立了基于相反方向累积的操作和背景值的优化的灰度新信息GOM(1,1)模型。它是灰色模型的新方法。该示例显示它具有比非新信息模型更高的精度。

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