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Application of Self-Organizing Maps to the Maritime Environment

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Information Fusion and Geographic Information Systems

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

Abstract

Self-Organizing Maps (SOMs), or Kohonen networks, are widely used neural network architecture. This paper starts with a brief overview of how SOMs can be used in different types of problems. A simple and intuitive explanation of how a SOM is trained is provided, together with a formal explanation of the algorithm, and some of the more important parameters are discussed. Finally, an overview of different applications of SOMs in maritime problems is presented.

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Author information

Authors and Affiliations

  1. Portuguese Naval Academy, Alfeite, Almada, 2810-001, Portugal

    Victor J. A. S. Lobo

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  1. Victor J. A. S. Lobo
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Correspondence to Victor J. A. S. Lobo .

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Editors and Affiliations

  1. 39, 14th Linia, V.O., 199178, St. Petersburg, Russia

    Vasily V. Popovich (Deputy Director of SPIIRAS for Research, Professor, Dr Sci Tech) (Deputy Director of SPIIRAS for Research, Professor, Dr Sci Tech)

  2. Naval Academy Research Institute, Lanveoc-Poulmic BP 600, F-29240, Brest Naval, France

    Christophe Claramunt

  3. GmbH Central European Institute of Technology Department of Urbanism, Transport, Environment and Information Society, CEIT ALANOVA gemeinnützige, Am Concorde Park 2, Gebäude F, A-2320, Schwechat, Austria

    Manfred Schrenk

  4. B1320 1176 Howell St., Newport, RI, 02841-1708, USA

    Kyrill V. Korolenko P.E. (Chief Scientist/NUWC Code 1543) (Chief Scientist/NUWC Code 1543)

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© 2009 Springer-Verlag Berlin Heidelberg

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Lobo, V.J.A.S. (2009). Application of Self-Organizing Maps to the Maritime Environment. In: Popovich, V.V., Claramunt, C., Schrenk, M., Korolenko, K.V. (eds) Information Fusion and Geographic Information Systems. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00304-2_2

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