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组合预测模型在农产品价格短期预测中的应用------以苹果为例的实证分析

王川1,赵俊晔1,赵友森2   

  1. 1.中国农业科学院农业信息研究所,北京 100081; 农业部农业信息  服务技术重点实验室,北京 100081; 2.北京市农业局信息中心,北京 100029
  • 收稿日期:2012-06-15 出版日期:2013-01-25 发布日期:2013-07-02

王川,赵俊晔,赵友森. 组合预测模型在农产品价格短期预测中的应用------以苹果为例的实证分析[J]. 系统科学与数学, 2013, 33(1): 89-96.

WANG Chuan, ZHAO Junye, ZHAO Yousen. THE APPLICATION OF COMBINATION MODEL ON SHORT-TERM PRICE  FORECASTING OF AGRICULTURE PRODUCTS---THE EMPIRICAL ANALYSIS OF APPLE PRICE[J]. Journal of Systems Science and Mathematical Sciences, 2013, 33(1): 89-96.

THE APPLICATION OF COMBINATION MODEL ON SHORT-TERM PRICE  FORECASTING OF AGRICULTURE PRODUCTS---THE EMPIRICAL ANALYSIS OF APPLE PRICE

WANG Chuan1, ZHAO Junye1, ZHAO Yousen2   

  1. 1.Agricultural Information Institute of Chinese Academy of Agricultural Science, Beijing  100081; 2.Information Center of Beijing Municipal Bureau of Agricultural, Beijing  100029
  • Received:2012-06-15 Online:2013-01-25 Published:2013-07-02
以我国苹果批发市场价格为研究对象,利用2006年7月7日至2012年3月30日期间的300个周数据作为分析样本,通过对时间序列的平稳性、趋势性、季节性、异方差等数据特征进行统计检验,筛选出双指数平滑模型、Holt-Winters乘法模型、ARIMA(1,1,4)模型为我国苹果市场价格短期预测的适用模型,以此为基础,以误差平方和最小为最优准则建立了组合预测模型.经对未来3期的苹果市场价格开展预测,结果表明,组合预测的精度要高于单项时间序列模型,组合预测方法完全适用于农产品市场价格的短期预测.
Taking the apple price of wholesale market in China as study object, using the data of 300 weeks from 2006-7-7 to 2012-3-30 as analysis  sample, by statistic test of the data characteristics such as Smooth, Trend,  Seasonality, Heteroskedasticity etc. of time series, we choose the Double  exponential smoothing model, the multiplicative model of Holt-Winters,   ARIMA (1,1,4) model as applicable model of short term forecast of apple market   price in China. Based on these results, we establish the Combination Forecasting   Model with the least sum of error square as optimal criteria. By carrying out    the forecast of apple market price in future three periods, the results show that   the accuracy of combination forecasting is higher than individual time series model,    and the combined forecasting method is fully applicable to the short-term forecasts of   agricultural products market price.

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