Winter Wheat Yield Prediction Model in the Yellow-Huaihe-Haihe River Region Based on CNN-LSTM
Winter wheat is one of the most crucial cereal crops in China,and the accurate prediction of its yield plays a significant role in guiding agricultural production and ensuring food security.This paper leverages the feature extraction capability of CNN and the advantage of LSTM in capturing long-term dependencies in time series to propose a CNN-LSTM prediction model.A dataset was constructed using the winter wheat yield and related meteorological indicators from 35 counties in the Yellow-Huaihe-Haihe River area from 2015 to 2022.This model was then applied to predict the winter wheat yield in the selected areas.The results indicate that the accuracy of the CNN-LSTM prediction model surpasses that of other models,with an R2 of 96.91%in the test set,thoroughly demonstrating the model's effectiveness in predicting the yield of winter wheat.