Research On Product Demand Forecasting Method Of M Company

With the advancement of data science,demand forecasting has become the foundation of sup ply chains in various industries.It is not only an empirical prediction,but also a data-based decision.T herefore,demand prediction technology based on data mining has emerged and has been favored by many enterprises.Its application can help enterprises better grasp future market changes and improve their competitiveness.This article takes M Company as the research object and analyzes the current situation and existing problems of M Company’s demand forecasting based on relevant theories of demand forecasting.Afterwards,by sorting out the influencing factors related to product demand prediction,collecting historical data for analysis and processing,the data is divided into four main feature groups:time,product features,target quantity trends,and environmental factors.A feature selection method based on tree models is used to select the optimal feature subset,in order to reduce the complexity of model training.Afterwards,a demand prediction model based on LSTM,RF,and XGBoost was constructed,and the model parameters were optimized using the Adam optimizer and Bayesian optimization to improve the model performance.The experimental results show that the prediction performance of single models is not significantly different,and they all have good generalization ability.However,when the fluctuation is strong,their performance will be different.In order to further improve the prediction accuracy of the model,three single models,LSTM,RF,and XGBoost,were used as the first layer base model,and multiple linear regression was used as the second layer metamodel.A demand prediction model based on Blending model fusion was constructed.The results show that its evaluation indicators are superior to the three single models.Multi model fusion not only makes full use of the advantages of a single model,but also improves its prediction accuracy and generalization ability.Finally,in order to ensure the orderly progress of demand forecasting work,M Company’s demand forecasting guarantee measures have been proposed.This includes measures to ensure demand forecasting data,clarify the collaborative forecasting workflow,and clarify the responsibilities and functions of each department.At the same time,measures such as evaluating and assessing demand forecasting have been proposed.The research results indicate that the demand prediction model proposed in this article can meet the needs of M Company’s product demand prediction work,and combined with various guarantee measures,it is convenient to provide decision support for subsequent production planning,inventory management,and other work.