中国农业大学学报2011，Vol.16Issue(2)：172-178,7.
农产品市场价格短期预测方法与模型研究——基于时间序列模型的预测
Study on short-term forecasting methods and modeling of agro-product market price: Forecasting based on the time series models
摘要
Abstract
In order to improve the predictability of agro-product market price and to take measures to reduce price fluctuation,this study selected the wholesale price of tomatoes as an object and employed the five methods, the seasonal dummy variables,the Census X12 method,the moving average method,the Holt-Winters seasonal exponential smoothing method and the SARIMA, to establish short-term forecasting models. A combination forecasting model was established and the weights used in the model were calculated according to the single model prediction error. The results showed that the error of single model fluctuated greatly and the accuracy declined with longer forecast period.Mean absolute percent error (MAPE) of the five single models in forecasting evaluation for 2009 is about 10％ ,of which the Holt-Winters seasonal exponential smoothing model has the lowest MAPE of 6. 81％. When forecast period is ahead of 3 months, the accuracy of the SARIMA model was the highest which was more than 95％. On the basis of empirical analysis, this study used the combination forecast method to predict the tomatoes market price in 2010.关键词
农产品/市场价格/预测模型分类
管理科学引用本文复制引用
李干琼,许世卫,李哲敏,董晓霞..农产品市场价格短期预测方法与模型研究——基于时间序列模型的预测[J].中国农业大学学报,2011,16(2):172-178,7.基金项目
国家"十一五"科技支撑计划重点项目(2009BADA9B01) （2009BADA9B01）
中央级公益性科研院所基本科研业务费专项(2010-J-11) （2010-J-11）
