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Functional coefficient autoregressive time series modeling based on fuzzy inference method

机译:基于模糊推理方法的功能系数自回转时间序列建模

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Functional coefficient autoregressive model is a class of useful nonlinear time series models. A new approach based on fuzzy inference modeling method for the estimation of the coefficient functions is proposed in this paper. A corresponding algorithm which is easy to be realized is designed. Besides, two typical simulation examples are studied, the estimated errors of which are minor than other models results. And the performance of forecasts on the proposed models has high degree of accuracy, which illustrates the validity of the method further.
机译:功能系数自回归模型是一类有用的非线性时间序列模型。本文提出了一种基于模糊推理建模方法的新方法,提出了估计系数函数的估计方法。设计了易于实现的相应算法。此外,研究了两个典型的仿真实例,估计误差是比其他模型的结果。预测对所提出的模型的性能具有高度的精度,其说明了该方法的有效性进一步。

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