基于多元回归分析的农作物产量估测模型研究

The Crop Yield Estimation Model Based on Multiple Regression Analysis

农作物产量的估测关系到粮食调度、粮食市场价格平衡、农业结构调整等众多方面。为此,结合多元回归分析,构建农作物产量估测模型。该模型构建先是利用灰度关联分析寻找影响农作物产量的主导因素,然后以主导因素数据作为输入,构建农作物产量的多元线性回归估测模型,得出农作物产量估测值。结果表明:通过本模型进行2017—2019年3年间东北3个省玉米总产量估测,得出玉米预测产量与实际产量之间的误差均小于1%,说明该模型的估测准确性较高,具有广泛的应用前景。

Crop yield estimation is related to many aspects,such as grain scheduling,grain market price balance,agricultural structure adjustment and so on.Therefore,combined with multiple regression analysis,this paper constructed a crop yield estimation model.In this model,the author used gray correlation analysis to find the leading factors that affect crop yield,and then used the data of the leading factors as the input to construct the multiple linear regression estimation model of crop yield and get the estimated value of crop yield.The results show that:by using this model to estimate the total yield of maize in the three northeast provinces of China from 2017 to 2019,the error between the predicted yield and the actual yield is less than1%,indicating that the model has high accuracy and wide application prospect.