基于GM(1,1)模型的四川粮食产量预测研究

中国人口众多，粮食安全关系到国计民生，加强粮食产量预测有利于确保粮食安全。根据2001—2015 年四川粮食产量的历史数据，运用灰色系统理论，建立基于弱化缓冲算子的GM(1,1)预测模型，通过残差、级比偏差、关联度、后验差检测、模拟数据检查对模型的合理性和精度进行误差检验，并应用模型预测未来3 年的粮食产量。研究结果表明，灰色系统理论GM(1,1)适用于粮食产量预测且具有较高的精度。预测了2016、2017、2018 年的粮食产量同比增长分别为-2.11%、-0.39%和1.21%，由此得出未来粮食产量将在波动中增长。

Prediction of Grain Yield of Sichuan Based on GM(1,1) Model

China has a large population, and food security is a major event relating to people's livelihood. Strengthening grain yield prediction can ensure food security. Based on historical data of grain yield in Sichuan from 2001 to 2015, we adopted grey system theory and set up GM (1, 1) prediction model on the basis of the weakening buffer operator, then used four error checking methods, including residual error, grade ratio deviation, correlation degree and posteriori error to test the reasonability and the prediction accuracy. Then we applied GM (1, 1) prediction model to predicting the grain yield in future three years. Test results indicate that the grey system theory is appropriate when it is applied to grain yield prediction and has high prediction accuracy. According to GM (1, 1) prediction model, the grain yield of the year 2016, 2017, 2018 will increase by-2.11%,-0.39%and 1.21%respectively year on year. It can be concluded that the grain yield of Sichuan will increase in fluctuation in the near future.