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Improved unequal interval grey model and its applications

机译:改进的不等间隔灰色模型及其应用

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摘要

A new method to improve prediction precision of GM(1, 1) model with unequal time interval is presented. The grey derivative is multiplied by a parameter to guarantee the time response function satisfying approximately exponential function distribution. To simplify the process of parametric estimation, an approximate value is taken for the multiplied parameter. Then the estimators of coefficient of development and grey action quantity can be derived. At the same time, the principle of the new information priority is also considered. We take the last item of the first-order accumulated generation operator (1-AGO) on raw data sequence as the initial condition in the time response function. Then the new information can be taken full advantage of through the improved initial condition. Some properties of this new model are also discussed. The presented method is actually a combination of improvement of grey derivative and improvement of the initial condition. The results of an example indicate that the proposed method can improve prediction precision prominently.
机译:提出了一种提高时间间隔不相等的GM(1,1)模型预测精度的新方法。将灰色导数乘以一个参数,以确保时间响应函数满足近似指数函数分布。为了简化参数估计的过程,对相乘后的参数取一个近似值。然后可以得出发展系数和灰色行动量的估计量。同时,还考虑了新信息优先权的原则。我们将原始数据序列上的一阶累积生成算子(1-AGO)的最后一项作为时间响应函数中的初始条件。然后,可以通过改善初始条件来充分利用新信息。还讨论了此新模型的某些属性。提出的方法实际上是改进灰色导数和改进初始条件的组合。算例结果表明,该方法可以显着提高预测精度。

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