Advertisement

Application of Genetic Algorithm for Component Optimization to Deploy Geoprocessing Web

  • Sujit Kumar Behera
  • Lalit Kumar Behera
  • Payodhar Padhi
  • Maya Nayak
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 308)

Abstract

Spatial data infrastructures served through the Web combined with the ever increasing network and telecommunication capabilities, and made geospatial data largely available over the last few decades. In addition, providing semantic specifications to geospatial information, data sharing and interoperability have also been achieved. Consequently, effective and efficient implementation of the Web processing, data processing methods for geospatial information extraction, and knowledge discovery over the Web are a major challenge for various domains. This paper provides a basic framework to optimize the various components associated with the geoprocessing implementation using genetic algorithm

Keywords

Geoprocessing Component optimization Genetic algorithm 

References

  1. 1.
    Kiehle, C., Greve, K., Heier, C.: Requirements for next generation spatial data infrastructures-standardized web based geoprocessing and web service orchestration. Trans. GIS 11(6), 819–834 (2007)CrossRefGoogle Scholar
  2. 2.
    Tsou, M., Buttenfield, B.: A dynamic architecture for distributing geographic information services. Trans. GIS 6(4), 355–381 (2002)CrossRefGoogle Scholar
  3. 3.
    Zhao, P., Di, L., Yu, G.: Building asynchronous geospatial processing work-flows with web services (2011)Google Scholar
  4. 4.
    Abel, D., Taylor, K., Ackland, R., Hungerford, S.: An exploration of GIS architectures for internet environments. Comput. Environ. Urban. Syst. 22(1), 7–23 (1998)CrossRefGoogle Scholar
  5. 5.
    Berners-Lee, T., Hall, W., Hendler, J., Shadbolt, N., Wietzner, D.: Creating a science of the web. Science 311(5788), 769–771 (2006)CrossRefGoogle Scholar
  6. 6.
    Zhao, P., Di, L., Yu, G.: Building asynchronous geospatial processing work-flows with web services. Comput. Geosci. 39(2), 34–41 (2012)CrossRefGoogle Scholar
  7. 7.
    Zhao, P., Yu, G., Di, L.: Geospatial web services. In: Hilton, B. (Ed.), Emerging Spatial Information Systems and Applications, pp. 1–35. Idea Group Publishing, Hershey (2006)Google Scholar
  8. 8.
    Ji, Z., Li, Z., Ji, Z.: Research on genetic algorithm and data information based on combined framework for nonlinear functions optimization. Proc. Eng. 23, 155–160 (2011)CrossRefGoogle Scholar
  9. 9.
    Mezura-Montesa, E., Coello Coello, C.A.: Constraint-handling in nature-inspired numerical optimization: past, present and future. Evol. Comput. 1, 173–194 (2011)CrossRefGoogle Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  • Sujit Kumar Behera
    • 1
  • Lalit Kumar Behera
    • 2
  • Payodhar Padhi
    • 2
  • Maya Nayak
    • 3
  1. 1.AricentBengaluruIndia
  2. 2.Konark Institute of Science and TechnologyJatni, BhubaneswarIndia
  3. 3.Orissa Engineering CollegeJatni, BhubaneswarIndia

Personalised recommendations