A neural network based method for classification of meteorological data

Abstract

A neural network based method for classification of meteorological data is proposed in the paper. The method consists of two phases. First, a non-linear projection of the data space is performed by means of radial basis functions. The neural gas algorithm is used for determining locations of the basis functions. Second, a nonlinearly projected data is allocated to different classes by means of a competitive network layer. Nonlinear data transformation was necessary for obtaining linear separability of 6 classes of the meteorological data defined in 8 dimensions.