Grain yield prediction based on GA-XGBoost algorithm in Henan Province
The food issue is related to the fate of the country,and the food issue is the foundation of the national economic de-velopment foundation.The change of grain output is directly related to the food security and the optimization and adjustment of agri-cultural structure in our country.In order to improve the accuracy and efficiency of grain production forecasting in Henan Province,relevant data such as grain production in Henan Province were summarized and analyzed,and the main factors affecting grain pro-duction in Henan Province were determined by Pearson correlation impact analysis.Aiming at the problem that XGBoost model is easy to overfit and inaccurate in prediction,genetic algorithm(GA)was introduced to optimize its learning rate and tree depth,so as to predict grain yield in Henan Province more accurately.The simulation results show that compared with the traditional XGBoost model,GA-XGBoost model has higher prediction accuracy,RMSE is only 0.034.Therefore,GA-XGBoost forecasting model can make more accurate prediction of grain yield.
NETL
NSTL
万方数据
