Skip to main content

Demand Forecast of Regional Tourism Based on Variable Weight Combination Model

  • Conference paper
Book cover Information Computing and Applications (ICICA 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 308))

Included in the following conference series:

Abstract

The forecast of regional tourism demand is a complicated system. The developmental change possesses the dual trend of increasing and fluctuation. So it is very difficult to forecast. Based on the data feature of regional tourism demand, three forecast models are adopted , namely the exponential smoothing prediction , the gray prediction and the exponential smoothing prediction. Combined the characteristics of three forecast methods, a forecast model with weight-varying combination is proposed. The exactness of the combination forecast model is validated through the contrast and analysis with practical cases. Estimated results show that the weight-varying combination forecast model can overmatch the single forecast model. The weight-varying combination model is valuable for the forecast of regional tourism demand with the uncertainty system.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bates, J.N., Granger, C.W.J.: Combined forecasting. Journal of Operational Research 20, 451–460 (1969)

    Article  Google Scholar 

  2. Zhou, R., Duan, X.: Optimal Combined Load Forecast Based on the Improved Analytic Hierarchy Process. In: Proceedings of the International Conference on Power System Technology, Power Con 2002, vol. 2, pp. 1096–1100 (2002)

    Google Scholar 

  3. Smeral, E., Wuger, M.: Does complexity matter? Methods for improving forecasting accuracy in tourism: The case of Australia. Journal of Travel Research 44, 100–110 (2005)

    Article  Google Scholar 

  4. He, H., Yu, Z.: Prediction of Pavement Roughness with Variable-weight Combination Forecasting Method of S-type Curves. Highway Engineering 8, 25–128 (2008)

    Google Scholar 

  5. Li, J.: Local Weighting Least-square Method of Weight-varying Combination of Forecast Models. Statistics & Information Forum 5, 44–47 (2007)

    Google Scholar 

  6. Zhang, W., Liao, Y.: Stock Market Volatility Forecasting Based On Weight-Varying Combination Model. Economic Research Guide 4, 27–28 (2007)

    MATH  Google Scholar 

  7. Wang, L., Jiang, L., Xi, J.: RBF Variable Weight Combined Forecasting Method of Aero-Engine Wear Trend. Journal of Shenyang Institute of Aeronautical Engineering 27(3), 26–29 (2010)

    Google Scholar 

  8. Pang, X., Wang, P.: Application of a New Variable-weight Combined Forecasting. Zhong Guo Dian Li Jiao Yu 3, 156–158 (2007)

    Google Scholar 

  9. Cui, L., Xu, M., Ke, H.: Prediction and Application Based on Variable Weight Combination Forecasting Method. Statistics and Decision 15, 37–39 (2009)

    Google Scholar 

  10. Yin, S., Yang, L.: Review of Tourism Demand Forecasting Methods and Models. Journal of Gansu Economic Management Institute 21(3), 24–27 (2008)

    MATH  Google Scholar 

  11. Qinhuangdao Tourism Statistical Yearbook (2002-2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Liu, L. (2012). Demand Forecast of Regional Tourism Based on Variable Weight Combination Model. In: Liu, C., Wang, L., Yang, A. (eds) Information Computing and Applications. ICICA 2012. Communications in Computer and Information Science, vol 308. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34041-3_92

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34041-3_92

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34040-6

  • Online ISBN: 978-3-642-34041-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics