On Terrain Coverage Optimization by Using a Network Approach for Universal Graph-Based Data Mining and Knowledge Discovery

  • Michael Preuß
  • Matthias Dehmer
  • Stefan Pickl
  • Andreas Holzinger
Conference paper

DOI: 10.1007/978-3-319-09891-3_51

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8609)
Cite this paper as:
Preuß M., Dehmer M., Pickl S., Holzinger A. (2014) On Terrain Coverage Optimization by Using a Network Approach for Universal Graph-Based Data Mining and Knowledge Discovery. In: Ślȩzak D., Tan AH., Peters J.F., Schwabe L. (eds) Brain Informatics and Health. BIH 2014. Lecture Notes in Computer Science, vol 8609. Springer, Cham

Abstract

This conceptual paper discusses a graph-based approach for on-line terrain coverage, which has many important research aspects and a wide range of application possibilities, e.g in multi-agents. Such approaches can be used in different application domains, e.g. in medical image analysis. In this paper we discuss how the graphs are being generated and analyzed. In particular, the analysis is important for improving the estimation of the parameter set for the used heuristic in the field of route planning. Moreover, we describe some methods from quantitative graph theory and outline a few potential research routes.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Michael Preuß
    • 1
  • Matthias Dehmer
    • 1
  • Stefan Pickl
    • 1
  • Andreas Holzinger
    • 2
    • 3
  1. 1.Institute for Theoretical Computer Science, Mathematics & Operations ResearchUniversity of the German Federal Armed Forces MunichGermany
  2. 2.Research Unit HCI, Institute for Medical InformaticsMedical University GrazAustria
  3. 3.Institute for Information Systems and Computer MediaGraz University of TechnologyAustria

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