Forecasting Consumer Confidence Index Based on Radial Basis Function Neural Network

Abstract:

Consumer confidence index (CCI) is a basic economic parameter of country economic development changes and is observed in the point of view of consumers. To predict the CCI for the next few months, Radial basis function (RBF) neural network is introduced. Compared with the BP network, the simulation results obtained by RBF make more accurate precisions with better fitting effects. From the results of our prediction, the analysis for the tendency of CCI in the future is also obtained.

• Periodical: Applied Mechanics and Materials (Volume 596)
• Pages: 200-203
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.596.200
• Online since: July 2014
• Authors: Hai Yan Xie*, Guo Yan Chen, Zhen He, De Peng Zhao
• Keywords: Consumer Confidence Index, Forecast, Radial Basis Function (RBF) Neural Network

References

[1] N. Yang, J.Y. Wang, Guide to Business, 2012(3): pp.7-8. (in Chinese).

[2] Q. Wu, J.B. Ou, Commercial Research, 2010(9): 142-175. (in Chinese).

[3] H. Zhang, . Finance View, 2012(01): 83. (in Chinese).

[4] X.F. Yang, Times Finance, 2012(3B): 314. (in Chinese).

[5] Juan Gao, Principle of Artificial Neural Network and Simulation (2nd edition), China Machine Press, Beijing, 2007, in press.

[6] D.M. Zhao, H.F. Liu, C.G. Liu, Computer Engineering and Applications, 2007, 43(1): 139-141. (in Chinese).