Abstract:
The second part of the article is devoted to the top-level algorithm models. Modeling of cellular automaton structure and forecasting are realized on the upper level. The genetic algorithm which determines the interaction of cells with all the nearest neighbors is proposed for learning linear cellular automaton. The mathematical apparatus of the theory of fuzzy sets is adequately involved in the article. Each stage of two-level cellular automaton predictive model is accompanied by a brief overview of the developed algorithms.