Methods of Artificial Intelligence used for Transforming a System of Coordinates

The article discusses the problem of transformation in the form of the function f : R-2 -> R-2 as dependence between the coordinates [x, y] of the original system and the coordinates [X, Y] of the secondary system. The task of the transformation of[X, Y] = f( x, y) technically understood as the transformation of a system of coordinates has been solved by means of the feed-forward neural networks of the sigmoidal type, radial neural networks, recurrent cascade neural networks, and neuro-fuzzy systems with the use of the Takagi-Sugeno-Kang model. The numerical procedures applied make it possible to obtain a level of accuracy of the task equivalent to the cartographic accuracy of pictures in the Spatial Information Systems.