Concept of Neural Model of the Sea Bottom Surface
Jacek Łubczonek, Andrzej Stateczny · 2003
This paper presents concept of neural model of the sea bottom surface, which could be implemented in marine numerical maps. The model consists of self-organizing network and set of trained networks used in surface approximation. Self-organizing networks firstly solves problem of division of data points into training subsets. Secondly it classifies any input data to one of approximating network. Set of approximating networks is used to calculate depth value at any coordinates of point within surface domain. An example illustrates reconstruction of surface based on neural model of bottom surface. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.