• DocumentCode
    2068767
  • Title

    One dimensional Self-Organizing Maps to optimize marine patrol activities

  • Author

    Lobo, Victor

  • Author_Institution
    Portuguese Naval Acad. & Fernando Bacao, ISEGI-UNL, Lisboa, Portugal
  • Volume
    1
  • fYear
    2005
  • fDate
    20-23 June 2005
  • Firstpage
    569
  • Abstract
    A method for planning routes for patrol vessels is proposed. This method is based on a Self-Organizing Map (SOM) solution for the Travelling Salesman Problem (TSP), although with significant changes. The locations of reported Search and Rescue (SAR) requests, together with the locations of reported occurrences of illegal fishing activities are used as guidelines for designing the path vessel should take. However, instead of forcing the patrol routes to pass exactly in those locations, as would happen in a TSP, the proposed method uses the locations as density estimators for where the patrol effort should be placed. It then obtains a patrol route that passes through the areas with greater density. We show the behaviour of the proposed method on artificial data, and then apply the method to some data from the Portuguese Navy, obtaining possible routes for its patrol vessels.
  • Keywords
    aquaculture; geophysics computing; marine vehicles; self-organising feature maps; travelling salesman problems; 1D Self-Organizing Map; Portuguese Navy; SOM; Search and Rescue request; TSP; Travelling Salesman Problem; density estimator; illegal fishing activities; marine patrol activities; path vessel design; patrol route; patrol vessels; Cities and towns; Economic forecasting; Environmental economics; Guidelines; Monitoring; Optimization methods; Protection; Self organizing feature maps; Strategic planning; Traveling salesman problems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Oceans 2005 - Europe
  • Conference_Location
    Brest, France
  • Print_ISBN
    0-7803-9103-9
  • Type

    conf

  • DOI
    10.1109/OCEANSE.2005.1511777
  • Filename
    1511777