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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
verfasst von : Andrzej Stateczny, Marta Wlodarczyk-Sielicka
Erschienen in: Rough Sets and Intelligent Systems Paradigms
Verlag: Springer International Publishing
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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.