Application of LSTM-PROPHET mixed model in material reserve demand forecasting
The LSTM-Prophet mixed model was established to predict the daily material consumption of Company A and pro-vide reference for the daily material reserve of the workshop.The data set was derived from the actual daily material consumption of Company A since 2015.The experimental results showed that the MAE value,MAPE value and R2 value of the LSTM-Prophet mixed model were 40.905,0.044 and 0.863,all of which were better than the LSTM model,Prophet model and ARIMA model.It is verified that the LSTM-Prophet hybrid model has better prediction accuracy and can be better applied to industrial scenarios.
LSTM modelProphet modeltime series data predictionmixed model prediction
NETL
NSTL
万方数据
维普
