Design of the Models of Neural Networks and the Takagi-Sugeno Fuzzy Inference System for Prediction of the Gross Domestic Product Development

The paper presents the possibility of the design of frontal neural networks and feed-forward neural networks (without pre-processing of inputs time series) with learning algorithms on the basis genetic and eugenic algorithms and Takagi-Sugeno fuzzy inference system (with pre-processing of inputs time series) in predicting of gross domestic product development by designing a prediction models whose accuracy is superior to the models used in praxis [1,2]. Key-Words: Gross domestic product, frontal neural networks, feed-forward neural networks, Takagi-Sugeno fuzzy inference systems, genetic and eugenic algorithms, EuSANE algorithm.