摘要
为了准确预测蔬菜价格,从蔬菜价格具有季节性变化的特性出发,采用SARIMA模型方法对平菇价格进行了预测分析。结果表明:SARIMA(2,1,3)(1,1,1)12模型对平菇价格的模拟预测效果较好,平均模拟预测误差为11%,6个月的短期实际预测平均误差为16%。SARIMA模型对农产品价格进行预测分析具有一定的可行性。
The price of oyster mushroom was predicted and analyzed by using seasonal ARIMA model and proceeding from seasonal change of vegetable price to predict vegetable price accurately.The results showed that the model of SARIMA （2,1,3） （1,1,1） 12 exactly fitted the oyster mushroom price in the previous months.Its average errors rate was 11％,the average short-term actual forecast error of six months was 16％.Applying SARIMA model in predicting agricultural product price was of a certain feasibility
出处
《贵州农业科学》
CAS
北大核心
2013年第11期202-204,209,共4页
Guizhou Agricultural Sciences
基金
北京市自然科学基金项目"基于遗传算法的蔬菜市场价格神经网络预测模型研究"(9093019)
关键词
季节时间序列模型
平菇
农产品价格
预测
时间序列
seasonal ARIMA model
oyster mushroom
agricultural product price
forecasting
time series
