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

doi:10.12341/jssms12022

系统科学与数学 ›› 2013, Vol. 33 ›› Issue (1): 89-96.DOI: 10.12341/jssms12022

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.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

PDF ( 683 ) 引用被引次数 ( 9 )

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.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.

关键词： 农产品, 市场价格, 短期预测, 组合预测.

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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