Adaptation of linear cellular automaton for solving the problems of forecasting on the basis of natural and economic time series

Abstract

Purpose: this article continues the study on mathematical methods of nonlinear dynamics utilization in the development and adaptation of mathematical methods and predictive models for the analysis of time series of winter wheat yields in the regions of southern Russia. Discussion: the authors chose a linear cellular apparatus was chosen as a main tool in order to demonstrate and predict the behavior of the observed system. The values of indicators of winter wheat yield in the regions of southern Russia are studied. The choice of data series was made due to the following fact – each contains a different number of statistics, and some of the studied series represent a small sample. It is shown that the preparation of a sufficiently accurate forecast is possible on the basis of a small amount of data. Results: this article reveals the applicability of using a linear cellular automaton for nonlinear dynamic systems forecasting, which solves the problem of so-called «small samples».