Application Of Combined Grey Model In Prediction Of Maize Yield In Black Soil Area

China has a vast territory and a large population.There are limited agricultural production materials in various regions,not abundant agricultural resources per capita and uneven distribution and so on.The existence of all kinds of circumstances shows that agriculture is one of the main factors that determine the rapid development of the national economy.Agriculture is the basic industry in China,and corn production plays an important role in Chinese agriculture.The process of agricultural production is a complex and open ecosystem.It uses grain production and production dynamics to guide grain production to be affected by external factors,and correctly and effectively predict future grain production and production,which is conducive to the development of Chinese agricultural production and the development of national industry.Agriculture is a dynamic uncertain system.In the system,data are often lacking and information is not perfect.Grey system can solve the modeling problem under such circumstances,and use grey system theory to achieve prediction,association and analysis.However,with the development of production practice,more and more new problems need to be solved by further theoretical knowledge.Based on the existing literature,this paper analyzes and studies the problems of data generation and model building in time series and grey system,and puts forward the application of combined grey system modeling in the prediction of Maize Yield in precision agriculture in our province.The main research is:(1)The present situation of maize production in Jilin Province,the time series algorithm and the theory of grey system theory are introduced.(2)According to the data of 20 years maize yield obtained from Jilin yearbook data,a time series prediction model is built,and a grey GM(1,1)model based on grey system theory is constructed.Two models were used to predict corn yield data in Jilin province for 20 years,and compared with the actual maize yield data to verify the validity of the model.(3)In view of the complex characteristics of maize yield,the combined grey model was used to predict the time characteristics of maize yield.The construction step of the combined grey prediction model is to transform the original data through the logarithmic function power function method.The time series data are processed into the grey model and the results are predicted.Finally,the prediction results are corrected by establishing the residual model.It is found that the prediction accuracy is higher,and the prediction effect of combined grey system prediction model on Maize Yield in Jilin is significantly better than that of single prediction model.