Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks

Abstract

The article presents a particular comparison of selected clustering algorithms of data obtained by interferometrie methods using artificial neural networks. For the purposes of the experiment original data from Szczecin Port have been tested. For collecting data authors used the interferometric sonar system GeoSwath Plus 250 kHz. GeoSwath Plus offers very efficient simultaneous swath bathymetry and side scan seabed mapping. During the use of Kohonen's algorithm, the network, during learning, use the Winner Take All rule and Winner Take Most rule. The parameters of the tested algorithms were maintained at the level of default. During the research several populations were generated with number of clusters equal 9 for data gathered from the area of 100m2. In the subsequent step statistics were calculated and outcomes were shown as spatial visualization and in tabular form.