Research on Forest Product Sales Price Prediction System Based on ARIMA and LSTM Hybrid Models
To improve the accuracy of forestry product sales price prediction,a forestry product sales price prediction system based on a hybrid model of ARIMA and LSTM is proposed.The system design analysis and database design ensure the overall performance of the system.By preprocessing historical data,the data quality has been improved.Use ARIMA model and LSTM residual prediction for price prediction,and integrate the two to obtain the final prediction result.The experimental results show that the prediction error of the system is controlled below 3,with higher accuracy and strong reliability,which can provide reference for predicting product price fluctuations.
forestry productsprice forecastARIMA modelLSTM model
NETL
NSTL
万方数据
