在分析自回归移动平均模型特点的基础上,建立了食用菌价格预测模型。充分发挥ARIMA时间序列模型可以根据研究指标从过去到现在的演变过程找出定量演变规律,并依据其进行预测的优势,对食用菌市场价格进行预测分析。通过对江苏省杏鲍菇价格样本序列的实证分析表明,该模型短期预测的精确度较高,从而证明了ARIMA模型用于食用菌价格预测的有效性,解决困扰农民的盲目生产和销售问题。 On the basis of analyzing the characteristics of the autoregressive moving average model, the edible mushroom price forecasting model was established. Making full use of the ARIMA time series model can find out the law of quantitative evolution according to the evolution of the research index from the past to the present and predict and analyze the market price of mushroom according to its predication. The empirical analysis of the sample sequence of Pleurotus eryngii in Jiangsu Province shows that the short-term forecast accuracy of this model is high, which proves the effectiveness of the ARIMA model in predicting the edible mushroom price and resolves the problem of blind production and sale of peasants.