A New Algorithm about Market Demand Prediction of Automobile

An extensive evaluation hierarchy model of automobile short-term demand was established to prevent the disadvantages of previous models mainly for single time series. The definition of extensive correlation evaluation was proposed, and then the method was discussed to reflect the correlation of factors on automobile demand. Utilizing extensive skills, factors and sub-factors were represented as correlation eigenmatrix which could ensure the level of each factor’s influences on automobile demand. Then short-term historical data was predicted while it was compared with existing data, the results show that the predictive error is less than 6%, which confirms the validation of predictive model. This study provides the foundations for government’s macroeconomic control and automobile manufacturers ’ production