Research on Precipitation Prediction Based on LSTM Neural Network
Accurate and effective rainfall prediction model is of great significance for agricultural water resources management.Taking the historical rainfall data of Xingxian County in Shanxi Province as the research object,this paper proposes a model method based on long short-term memory network(LSTM)combined with multi-feature input,and compares the prediction results with the measured rainfall data.The results show that the LSTM model with multiple features has a significant improvement in the evaluation index compared with the model only characterized by precipitation,showing better prediction performance.The LSTM model combined with multiple features can meet the actual needs of accurately predicting rainfall,which is of great significance for improving the efficiency of agricultural water resources management.
precipitationagricultural water conservancyLSTMfeature input
NETL
NSTL
万方数据
