Skip to main content

Research on Navigation Algorithm Model of Virtual Tourism System Based on GIS

  • Conference paper
  • First Online:
Big Data and Security (ICBDS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1563))

Included in the following conference series:

  • 1004 Accesses

Abstract

In recent years, with the rapid development of economy, tourism has increasingly become an important part of people’s life. Especially in recent years, thanks to the integration of modern information technology, virtual tourism is increasingly favored by the public. In a narrow sense, virtual tourism uses modern computer technology to model scenic spots or some cultural relics and community buildings with tourism value, and allows participants to experience the fun of tourism in a virtual environment with the help of information sensing equipment and objective carriers. This kind of tourism has the advantages of low cost, high efficiency and strong selectivity. However, in order to make consumers experience the fun of virtual tourism more conveniently and quickly, the research on this abstract network navigation algorithm has attracted more and more attention. Under this background, according to the virtual tourism intelligent selection system, this paper studies the navigation algorithm model in the virtual tourism system based on the Geographic Information System, and makes an empirical analysis with an example.

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 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
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

References

  1. Yue, Y.: An efficient implementation of shortest path algorithm based on Dijkstra algorithm. J. Wuhan Tech. Univ. Surv. Mapp. 24(3), 208–212 (1999)

    Google Scholar 

  2. Abdulrahman, A., Pilouk, M.: Spatial Data Modelling for 3D GIS. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-74167-1

    Book  Google Scholar 

  3. Amirebrahimi, S., Rajabifard, A., Mendis, P., Ngo, T.: A data model for integrating GIS and BIM for assessment and 3D visualisation of flood damage to building. Locate 15, 10–12 (2015)

    Google Scholar 

  4. Boada, I., Navazo, I., Scopigno, R.: Multiresolution volume visualization with a texture-based octree. Visual Comput. 17(3), 185–197 (2001)

    Article  Google Scholar 

  5. Chen, L.C., Wu, C.H., Shen, T.S., Chou, C.C.: The application of geometric network models and building information models in geospatial environments for fire-fighting simulations. Comput. Environ. Urban Syst. 45, 1–12 (2014)

    Article  Google Scholar 

  6. Zimmermann, T., Wirtz, H., Punal, O., et al.: Analyzing metropolitan-area networking within public transportation systems for smart city applications. In: International Conference on New Technologies. IEEE (2014)

    Google Scholar 

  7. Li, W., Zhao, Z.-K., Na, X.: Deep belief network based 3D models classification in building information modeling. Int. J. Online Eng. 11(5), 57–63 (2015)

    Article  Google Scholar 

  8. Devillers, O., Guigue, P.: Faster triangle-triangle intersection tests. Dissertation, INRIA (2002)

    Google Scholar 

  9. Chuck, E., Lee, J.-M., Jeong, Y.-S., et al.: Automatic rule-based checking of building designs. Autom. Constr. 18(8), 1011–1033 (2009)

    Article  Google Scholar 

  10. Funkhouser, T., et al.: A search engine for 3D models. ACM Trans. Graph. (TOG) 22(1), 83–105 (2003)

    Article  Google Scholar 

  11. Guttman, A.: R-trees: a dynamic index structure for spatial searching. ACM (1984)

    Google Scholar 

  12. Huang, G.-B., Zhu, Q.-Y., Siew, C.-K.: Extreme learning machine: theory and applications. Neurocomputing 70(1–3), 489–501 (2006)

    Article  Google Scholar 

  13. Choi, J., Choi, J., Cho, G., et al.: Development of open BIM-based code checking modules for the regulations of the fire and evacuation

    Google Scholar 

  14. Crane, K., Weischedel, C., Wardetzky, M.: Geodesics in heat: a new approach to computing distance based on heat flow. ACM Trans. Graph. 32(5), 13–15 (2013)

    Article  Google Scholar 

  15. Wang, J., Ying, S., Liu, Z., et al.: Route planning based on Floyd algorithm for intelligence transportation system. In: IEEE International Conference on Integration Technology, ICIT 2007. IEEE (2007)

    Google Scholar 

  16. Wei, D.: An optimized floyd algorithm for the shortest path problem. J. Networks 5(12), 1496–1504 (2010)

    Article  Google Scholar 

  17. Wei, D.: Implementation of route selection function based on improved Floyd algorithm. In: IEEE 2010 WASE International Conference on Information Engineering (ICIE), pp. 223–227 (2010)

    Google Scholar 

  18. Lin, S., Kernighan, B.W.: An effective heuristic algorithm for the traveling-salesman problem. Oper. Res. 21(2), 498–516 (1973). https://doi.org/10.1287/opre.21.2.498

    Article  MathSciNet  MATH  Google Scholar 

  19. Hasan, B.S., Khamees, M.A., Mahmoud, A.: A heuristic genetic algorithm for the single source shortest path problem. In: IEEE/ACS International Conference on Computer Systems and Applications. IEEE (2007)

    Google Scholar 

  20. Khemlani, L.: Building product models: computer environments supporting design and construction. Autom. Constr. 11(4), 495–496 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wang, J., Yang, S., Cheng, C. (2022). Research on Navigation Algorithm Model of Virtual Tourism System Based on GIS. In: Tian, Y., Ma, T., Khan, M.K., Sheng, V.S., Pan, Z. (eds) Big Data and Security. ICBDS 2021. Communications in Computer and Information Science, vol 1563. Springer, Singapore. https://doi.org/10.1007/978-981-19-0852-1_14

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-0852-1_14

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-0851-4

  • Online ISBN: 978-981-19-0852-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics