Analysis of Grain Yield Prediction Model in Liaoning Province

作者：Yin Guang Hua^*; Gu Jian; Liu Zuo xin; Hao Liang; Tong Na

来源：Conference on the Future Computer and Control Systems, 2012-04-21 to 2012-04-22.

• grain yield
• stepwise regression
• gray prediction method
• BP neural network
• forecast

Based on agricultural production data of Liaoning Province from 1980a to 2009a, using stepwise regression method, the gray prediction method, BP neural network, the grain yield prediction model was respectively established in Liaoning Province, China. The grain yield was predicted with these models, and models were compared. The results show that the yield forecasts relative error of the stepwise regression model, gray prediction model, BP neural network model are respectively: 3.41%, 6.59%, and 1.16%. Among the three models, the order of best fit is the BP neural network model, the less is the stepwise regression model, the least is the gray model. It was proved that the BP neural network model is optimum one with high correspondence degreed and high accuracy for food production forecast in Liaoning Province.

• 出版日期2012
• 单位中国科学院