灰色离散时变模型及其应用

L. Wu, Ying-Jian Qi, Zheng-peng Wu
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引用次数: 1

摘要

尽管灰色离散模型及其改进模型在一些领域得到了成功的应用,并取得了良好的效果,但有时预测结果可能不准确。通过引入二次时变项,得到一个灰色离散参数模型,称为二次时变参数离散灰色模型(简称QDGM(1,1))。研究了新模型的性质,得出QDGM(1,1)具有白指数律符合、线性律符合、二次律符合的结论。然后,对新模型的迭代起始值进行优化。最后,将新模型与使用相同数据实例的三种离散灰色模型进行比较。实验证明,该模型大大提高了仿真和预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Grey Discrete time-varying Model and Its application
Although the Grey Discrete Model and its improved models have been successfully employed in some fields and have promising results, the prediction results may be inaccurate sometime. We bring a grey discrete parameters model by introducing quadratic time-varying terms, which is called as quadratic time-varying parameters discrete grey model (referred to as QDGM (1, 1)). The paper investigates the properties of the new model, and concludes that QDGM (1, 1) possesses white exponential law coincidence, linear law coincidence, quadratic law coincidence. Then, we optimize the iterative starting value of the new model. Finally, the new model is compared with three discrete grey models using the same data instances. It is proved that the new model greatly improves the simulation and prediction precision.
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