Henan Province Express Quantity Forecast Based on SARIMA-LSTM Model
ZHANG Meiyue
GUI Haixia
Abstract：In order to realize the effective prediction of the development trend of express quantity in Henan Province,based on the time series theory,the study established SARIMA and SARIMA-LSTM combination models to respectively forecast the data of express quantity in Henan Province.Since it is difficult for the traditional time series model to capture the nonlinear features in the data series in express quantity forecasting,the study proposes a combined forecasting model combining the seasonal differential regression moving average model(SARIMA)and the long and short-term memory network(LSTM).By comparing and analyzing the prediction results of these two models,it is discovered that the SARIMA-LSTM combination model has higher accuracy in predicting the trend of express quantity.
Keywords：SARIMA-LSTM modelSARIMA modelexpress quantity
Publication Date：2024-05-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 96-103 )