Research On The Sales Status And Forecast Of Heavy Trucks In China Based On Method Of Factor Analysis

With the rapid development of China's economy and science and technology,the heavy truck industry has also developed rapidly.As an important branch of the automobile industry,it is often called the "barometer" of national economic development.However,the development of China's heavy truck industry is not only affected by the macro level of market economy and micro level of user demand,but also will accept the information age of science and technology Progress,improved infrastructure,macro-control and policy regulation of the automobile industry and many other aspects of the impact.Over the past ten years,the sales volume of heavy trucks in China has fluctuated greatly,with the sales volume breaking through the peak of one million vehicles in 2010 and 2017,and the cold winter trough in 2012 and 2015.If we can't accurately predict the future sales volume,there will be problems such as short supply or overstock of products.Therefore,it is necessary to study and explore the important factors that affect the sales volume of heavy trucks in China,carry out simulation,and then according to the prediction,combined with the actual situation,the steady progress and rapid development of the heavy truck industry.This paper first searches for the macro and micro factors that affect the sales volume of heavy trucks in China through literature review,and then describes the current situation of heavy trucks in detail with statistical analysis methods;secondly,it analyzes the heavy truck industry by SWOT,an important analysis method in management,and finds that the heavy truck industry in China has sound industry The three advantages of chain,low manufacturing cost and large market demand,as well as the disadvantages of technology and innovation,and vicious low price competition.Then,using machine learning method random forest to classify the above factors,the results show that PMI is the most critical factor affecting the sales volume of heavy trucks,followed by diesel price,total retail sales of social consumer goods,new construction area of real estate and industrial added value have an important impact on the sales volume of heavy trucks.The empirical results show that PMI and industrial added value have a significant positive impact on the sales volume of heavy trucks in China,and the policy variable governance over the limit has a significant positive impact on PMI and industrial added value.Finally,combining with the theoretical basis of principal component analysis,multiple linear regression and neural network prediction model,the data of heavy truck sales in China are analyzed and predicted.The quarterly data of sales volume and influencing factors from 2007 to 2017 are collected from the aspects of macro-economy,industrial commodity logistics,engineering construction,energy ore,price cost,policies and regulations,and the data are processed by natural logarithm,which makes the data more stable,convenient for calculation and modeling analysis.Through the principal component analysis of these data,the influence of heavy truck sales in China is obtained The main components F1 and F2 of the quantity.Secondly,the main components of the experiment are analyzed and extracted,the simulation model is established by qualitative analysis,and then the corresponding error is calculated according to the results of the model,and the applicability of the multiple linear regression model in the domestic heavy truck sales forecast is obtained.