Application Of Gray System In Automobile Marketing Prediction And Investment Decision

Traditional car sales forecasting, usually adopts a simplex model to estimate. The model, which just considers one kind of variety data trends, can't reflect complicated data nonlinear and characteristic. It is necessary to improve prediction accuracy. Automobile product project is simply chosen through the qualitative analysis of some questionnaires. There is a lack of scientific processing processes and evaluation foundations, which can't show the importance of the results. It is difficult to use in decision-making. Therefore, seeking for a method which is more scientific, objective and quantitative becomes more important.An integrated nonlinear-periodic prediction model of automobile sales, based on the theory of grey prediction model GM (1, 1), introduces periodic factor to simulate the characteristic of its periodic fluctuation. Compared with grey prediction model GM (1, 1), the results of the new prediction show that the model is feasible.The paper presents a grey relational assessment model to analyze product project by the analyzing grey relational degree and devising a relational matrix. And introduce analytic hierarchy process to ascertain indexes influence degree. Furthermore, this paper provides a reliable policy-making foundation for automobile enterprise to optimize product project.