Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 178-183.doi: 10.11896/jsjkx.200600104

• Big Data & Data Science • Previous Articles     Next Articles

Automobile Sales Forecasting Model Based on Convolutional Neural Network

LIU Ji-hua, ZHANG Meng-di, PENG Hong-xia, JIA Xing-ping   

  1. School of Business,Hubei University,Wuhan 430062,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:LIU Ji-hua,born in 1971,Ph.D.His main research interests include data mining and data analysis.
    ZHANG Meng-di,born in 1995,master.Her main research interests include data mining and data analysis.
  • Supported by:
    National Social Science Fundation of China(15BGL205) and National Natural Science Foundation of China(71902056).

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Abstract: Traditionally the kewords selection of web search data is a manual selection task.It is difficult to take all the keywords into consideration.Therefore,the deep learning method is introduced into the field of automobile sales prediction,and the deep learning model is used to extract features of web search data.At first,car-related keywords and online search volumes are collectedthrough web crawlers,and then a car sales prediction model of convolutional neural network is designed,based on the characteristics of web search data and sales data.The model is adopted to predict the sales of Volkswagen in the first half of 2019.The results show that the convolutional neural network can effectively predict car sales,and the accuracy of the prediction reaches 89.51%,compared with RBF,ARIMA and ARIMA+RBF model.Due to the impact of the Spring Festival and the implementation of new policies,it has the largest forecast error in February.However,it has the highest prediction accuracy in March as the market recovers.

Key words: Baidu index, Convolutional neural network, Sales forecast, Volkswagen

CLC Number: 

  • P315.69
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