Proceedings of the 2018 3rd International Conference on Humanities Science, Management and Education Technology (HSMET 2018)

The Application of BP Neural Network Model Based on Grey Relational Analysis in the Forecast of Automobile Demand in China's Provinces

Authors
Zhiping Lu, Zijuan Zhao
Corresponding Author
Zhiping Lu
Available Online June 2018.
DOI
10.2991/hsmet-18.2018.93How to use a DOI?
Keywords
Grey Relational Analysis; BP neural network; Forecast of Automobile Demand.
Abstract

Using the principle of grey relational analysis, the influencing factors of automobile demand in various provinces of China are screened, and then the BP neural network model is used to predict the demand for cars in various provinces in China, which greatly improves the prediction accuracy of neural networks and achieves good prediction results.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the 2018 3rd International Conference on Humanities Science, Management and Education Technology (HSMET 2018)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
June 2018
ISBN
10.2991/hsmet-18.2018.93
ISSN
2352-5398
DOI
10.2991/hsmet-18.2018.93How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhiping Lu
AU  - Zijuan Zhao
PY  - 2018/06
DA  - 2018/06
TI  - The Application of BP Neural Network Model Based on Grey Relational Analysis in the Forecast of Automobile Demand in China's Provinces
BT  - Proceedings of the 2018 3rd International Conference on Humanities Science, Management and Education Technology (HSMET 2018)
PB  - Atlantis Press
SP  - 477
EP  - 481
SN  - 2352-5398
UR  - https://doi.org/10.2991/hsmet-18.2018.93
DO  - 10.2991/hsmet-18.2018.93
ID  - Lu2018/06
ER  -