基于自适应ARMA模型的区域农业总产值构成研究与应用

    Composition of the gross output value of regional agriculture based on Adaptive Autoregressive Moving-Average Model and its application

    • 摘要: 由于噪声的存在并随时间累积,传统的自回归滑动平均模型(ARMA模型)不能直接应用于时间序列的中期预测。该文针对这种情况,提出了一种自适应的自回归滑动平均模型,将模型状态划分为无噪声的迭代模型和有噪声的观察模型,并根据迭代模型的特点,详细推导并完整给出了它的迭代求解公式,以便使其可以用于时间序列的中期预测,同时研究1985~2001年黄淮海平原农业、牧业与渔业产值预测模型,得到较理想的预测结果。并用所建模型对2001年产值进行外延预测,以期为区域农业结构调整提供理论依据。

       

      Abstract: Traditional autoregressive moving-average model can’t be applied directly medium-term forecast on time series because noise occurs and accumulates with time. Aiming at this problem, the paper proposes adaptive autoregressive moving-average model, which will be divided into noise-resistant iterative model and noise observational model. According to the iterative model's characteristic, the study deduces detailed and gives perfectly a series of iterative solution formula to apply directly medium-term forecast on time series. Finally by predicting output values of Farming, animal husbandry and fishery (1985-2001) in Huang-Huai-Hai plain, it suggests that the model is reliable, and then output values of 2002-2020 are predicted to provide agricultural structural adjustment with the theory foundation.

       

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