Research on Agricultural Environment Prediction Based on Deep Learning

The environmental security of agriculture is closely related to human beings. Analytical training of agricultural environmental data, forecasting its development trend, has positive significance for the protection of the safety of agricultural products. This paper proposes an agricultural environment prediction model based on deep learning LSTM (Long Short-Term Memory). By analyzing the agricultural environment parameters of the current period, the environmental parameters of the next moment can be predicted to achieve the purpose of early warning. The experimental results show that the model’s prediction results have little deviation from the actual values; on this basis, the LSTM model is optimized to replace LSTM with GRU(Gated Recurrent Unit), and the model is more effective.