Optimize BP Neural Network Structure on Car Sales Forecasts Based on Genetic Algorithm

DOI

10.2991/iiicec-15.2015.18How to use a DOI?

Keywords

prediction; (BP) neural network; linear correlation; genetic algorithm

Abstract

In order to improve the ability of BP neural network to fit complex functions, we improve the structure of the BP neural network and optimize the weights and thresholds of structure of the BP neural network based on genetic algorithm, then, training the BP neural network model to improve its capability, so, we can apply the model to the automobile sales forecasting system. We compare the prediction accuracy with the traditional BP neural algorithm, it shows that this method obviously fits the data better and has higher prediction accuracy to dates with significant linear correlation.

Copyright

© 2015, 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)

TY  - CONF
AU  - Jun Tang
AU  - Qing Wu
PY  - 2015/03
DA  - 2015/03
TI  - Optimize BP Neural Network Structure on Car Sales Forecasts Based on Genetic Algorithm
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 75
EP  - 79
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.18
DO  - 10.2991/iiicec-15.2015.18
ID  - Tang2015/03
ER  -