A Diversified Stacked Regression Model for Seasonal Product Demand Forecasting
With continuous changes in the global economic and industrial structure,effective supply chain management,especially accurate demand forecasting,has become the key for enterprises to cope with chal-lenges,avoid resource waste,reduce costs and improve operational efficiency.Therefore,it is of great signifi-cance to develop a forecasting model that is accurate,flexible and adaptable to market changes.In this paper,we proposed a diversified stacked regression model RXOEL-X,which combines the advan-tages of multiple algorithms including Blending Linear Regression,Random Forest(RF),Extreme Gradient Boost(XGBoost),Ordinary Least Squares(OLS),ElasticNet and Long Short-Term Memory Network(LSTM),and uses XGBoost as a secondary optimization model,which not only utilizes the powerful data analysis capabilities of machine learning,but also taps the robustness of traditional statistical methods and the nonlinear modeling capabilities of deep learning.The model fusion technology employed significantly im-proved the forecasting performance of the model,especially enabling it to effectively capture the seasonality and long-term dependence in the time series data,which is suitable for the demand forecasting of supply chains with obvious seasonality and trend characteristics.After introducing the construction and operation steps of RXOEL-X,the model is compared with five traditional simple models based on a set of public data,proving that the RXOEL-X model is better than the other models in terms of forecasting accuracy.At the same time,based on the actual sales data of a beverage company,the performance of the model was further tested and compared with 10 combination models,proving that the RXOEL-X model excelled in terms of prediction accuracy and data fitting ability.Through a sensitivity analysis,the forecasting accuracy of the RXOEL-X model was found to be virtually insusceptible to external influence,showing extremely high ro-bustness.In a temporal analysis,the model also performed best.The RXOEL-X model provides a frontier solution for the forecasting of seasonal product demand and a wide range of corporate supply chain management issues,which can help companies save costs and reduce in-ventory backlogs while improving their response speed to market changes and the overall flexibility of the supply chain.
NETL
NSTL
万方数据
