The Forecasting Research of Beijing Tourism Demand Based on the BP Neural Network

Yang Yu; Shi Min Wang

doi:10.4028/www.scientific.net/AMM.571-572.128

Paper Titles

Research on Audit Model of Users’ Operation Normalization Based on Graph Theory in Power System
p.109

Research on Design and Construction Method of Bent Functions
p.114

A Novelty Model for Reliability Assessment of Complex System
p.118

A Multi-Attribute Decision-Making Method Based on SPAOWA Operator
p.124

The Forecasting Research of Beijing Tourism Demand Based on the BP Neural Network
p.128

A Class of Singular Volterra-Fredholm Type Difference Inequality in Engineering
p.132

A Class of Volterra-Fredholm Difference Inequality with Weakly Singularity in Engineering
p.139

Application Research of the Polynomial Fitting Model in Transformation of Plane Rectangular Coordinate
p.143

Identification and Optimization of Soil Water Movement Model Based on GA under Drip-Irrigation
p.148

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 571-572The Forecasting Research of Beijing Tourism Demand...

The Forecasting Research of Beijing Tourism Demand Based on the BP Neural Network

Abstract:

This paper describes the basic principles and algorithm of the BP neural network and builds a forecasting model of Beijing tourism demand based on the BP neural network. The forecasting model can forecast and analyze the number of tourists in Beijing in the future, which using the MATLAB tools and the number of tourists in Beijing during 1994 to 2012 for empirical research. The results show that the forecasting model of Beijing tourism demand based on the BP neural network can forecast the number of tourists in Beijing in the future more accurately.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 571-572)

Pages:

128-131

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.571-572.128

Citation:

Cite this paper

Online since:

June 2014

Authors:

Yang Yu*, Shi Min Wang

Keywords:

BP Neural Network (BPNN), Forecasting, Tourism Demand

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Rumelhart D E and Mcclelland J L: Parallel Distributed Processing. The MIT Press, Cambridge, (1986).

Google Scholar

[2] Jianmin Zhang, Tao Wang and Zhongli Wang: Intelligent control theory and Application. Beijing: Metallurgical Industry Press, 2003: 90-105.

Google Scholar

[3] Haikun Wei: The theory and method of neural network structure design. Beijing: National Defence Industry Press, 2005: 25 -36.

Google Scholar

[4] Beijing Bureau of Statistics: Beijing statistical yearbook 2013. Beijing: China Statistics Press, 1994-(2012).

Google Scholar

[5] Kitahara M, Achenbach J D and Guo Q C: Neural network for Crack-depth Determination from Ultrasonic Back-ScatteringData. Review of Progress in Quantitative Evaluation, 1992(11): 701 -708.

DOI: 10.1007/978-1-4615-3344-3_90

Google Scholar

[6] Ronggui Luo and Minmei Huang: The forecasting research of the Yangtze River population based on the BP neural network. Journal of Wuhan University of Technology, 2004(10): 91-92.

Google Scholar