Research On Prediction Of Time Series Of Automobile Steel Price

Automobile industry as one of the world’s industrial advanced industries,with the development and progress of The Times,in recent years,is realizing the leap from traditional fuel vehicles to modern new energy vehicles,intelligent vehicles.As the main raw material of automobile industry,the price of steel occupies the first place of enterprise operation cost,which directly reflects the risk of price operation of automobile enterprises.How to know the factors affecting the price of automobile steel,predict and master the trend of price change is the focus of the managers of automobile enterprises.At the same time,it puts forward new optimization and improvement of the supply chain management of enterprises.Through the method of time series prediction,this paper provides advanced technical means to optimize and improve the internal management of automobile enterprises,which creates value for the development of enterprises,and improves the competitiveness in the industry at the same time.First of all,by reading and analyzing the relevant data of steel price prediction,combined with the summary of the current situation,characteristics and influencing factors of the conventional steel price,the paper applies to the study of the automobile steel price,through the acquisition and analysis of the historical price data,to clarify the validity of the automobile steel price prediction.At the same time,the paper lists the specific indicators affecting the price of automobile steel,and through the collected historical data,through the analysis of correlation and grey correlation degree,clearly obtains the key indicators affecting the price of automobile steel.Secondly,in order to better explain the rationality and accuracy of auto steel price prediction,this paper takes auto parts M enterprise as an example,through the acquisition and analysis of the relevant historical data of the enterprise,respectively with exponential smoothing,multiple linear regression and BP neural network three time prediction methods to establish the model for fitting and verification,and through the comparison and analysis of model prediction accuracy,The prediction effect of the three models is summarized respectively,and the conclusion that the BP neural network model is the best for predicting the price of automobile steel is drawn.Finally,through the research results of this paper to the auto parts M enterprise existing management problems are sorted out and discussed.This paper mainly aims to obtain the influencing factors of the price of automobile steel and the model with the optimal price prediction effect.The research results further provide a reasonable explanation for solving the problems of cost saving and supply chain management strategy formulation of automobile enterprises,and reduce the risk of price operation of enterprises.It can not only provide support for the managers of automobile enterprises in predicting the price of automobile steel.Make a reasonable management decision,and further explain the practical application value and significance of this study,to the automobile industry to steel price research provides a reference and reference.