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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process

  • Andrzej Stateczny
  • Marta Wlodarczyk-Sielicka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8537)

Abstract

The article presents the reduction problems of hydrographic big data for the needs of gathering sound information for Navigation Electronic Chart (ENC) production. For the article purposes, data was used from an interferometric sonar, which is a modification of a multi-beam sonar. Data reduction is a procedure meant to reduce the size of the data set, in order to make them easier and more effective for the purposes of the analysis. The authors‘ aim is to examine whether artificial neural networks can be used for clustering data in the resultant algorithm. Proposed solution based on Kohonen network is tested and described. Experimental results of investigation of optimal network configuration are presented.

Keywords

Kohonen network big data hydrography 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Andrzej Stateczny
    • 1
  • Marta Wlodarczyk-Sielicka
    • 2
  1. 1.Marine Technology Ltd.SzczecinPoland
  2. 2.Maritime UniversitySzczecinPoland

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