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

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Brain Informatics and Health (BIH 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8609))

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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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Author information

Authors and Affiliations

  1. Institute for Theoretical Computer Science, Mathematics & Operations Research, University of the German Federal Armed Forces Munich, Germany

    Michael Preuß, Matthias Dehmer & Stefan Pickl

  2. Research Unit HCI, Institute for Medical Informatics, Medical University Graz, Austria

    Andreas Holzinger

  3. Institute for Information Systems and Computer Media, Graz University of Technology, Austria

    Andreas Holzinger

Authors
  1. Michael Preuß
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  2. Matthias Dehmer
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  3. Stefan Pickl
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  4. Andreas Holzinger
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Editor information

Editors and Affiliations

  1. University of Warsaw and Infobright Inc., Poland

    Dominik Ślȩzak

  2. School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, Singapore

    Ah-Hwee Tan

  3. Computational Intelligence Laboratory, ECE Department, University of Manitoba, R3T 5V6, Winnipeg, MB, Canada

    James F. Peters

  4. Institute of Computer Science, University of Rostock, Rostock, Germany

    Lars Schwabe

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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. https://doi.org/10.1007/978-3-319-09891-3_51

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  • DOI: https://doi.org/10.1007/978-3-319-09891-3_51

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09890-6

  • Online ISBN: 978-3-319-09891-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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