A New Algorithm about Market Demand Prediction of Automobile


  •  Zhiming Zhu    
  •  Tao Chen    
  •  Tianmiao Shen    

Abstract

An extensive evaluation hierarchy model of automobile short-term demand was established to prevent thedisadvantages of previous models mainly for single time series. The definition of extensive correlationevaluation was proposed, and then the method was discussed to reflect the correlation of factors on automobiledemand. Utilizing extensive skills, factors and sub-factors were represented as correlation eigenmatrix whichcould ensure the level of each factor’s influences on automobile demand. Then short-term historical data waspredicted 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’smacroeconomic control and automobile manufacturers’ production.


This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1918-719X
  • ISSN(Online): 1918-7203
  • Started: 2009
  • Frequency: quarterly

Journal Metrics

h-index (February 2018): 38

i10-index (February 2018): 174

h5-index (February 2018): 22

h5-median (February 2018): 33

Learn more

Contact