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A Novel Fractional-Order Grey Prediction Model and Its Modeling Error Analysis

机译:一种新型的分数阶灰色预测模型及其建模误差分析

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Based on the grey prediction model GM(1,1), a novel fractional-order grey prediction model is proposed and its modeling error is systematically studied. In this paper, exponential data sequences are generated for numerical simulation. Via the numerical simulation method, the mean absolute percentage error (MAPE) of the fractional-order GM(1,1) with different values of order and development coefficient is compared to the GM(1,1) and the discrete GM(1,1). The error distribution of the sequences of exponential data is given. The GM(1,1) and the direct modeling GM(1,1) are both special cases of the fractional-order GM(1,1). The conclusion is helpful to further optimize the grey model using fractional-order operators and to expand the applicable bound of GM(1,1).
机译:基于灰度预测模型GM(1,1),提出了一种新型的分数阶灰度预测模型,并对其建模误差进行了系统的研究。在本文中,生成指数数据序列以进行数值模拟。通过数值模拟方法,将具有不同阶数和展开系数值的分数阶GM(1,1)的平均绝对百分比误差(MAPE)与GM(1,1)和离散GM(1, 1)。给出了指数数据序列的误差分布。 GM(1,1)和直接建模GM(1,1)都是分数阶GM(1,1)的特例。该结论有助于进一步使用分数阶算子优化灰色模型,并扩展GM(1,1)的适用范围。

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