Dynamic-Stochastic Modeling of Natural Processes

Abstract

We propose a method for the construction of dynamic-stochastic models of natural systems based on the assimilation of the data of observations in the prognostic equations of coupled processes. In these models, the method of adaptive balance of causes is used to deduce evolutionary equations of the analyzed processes and assimilate the data of observations in these equations. The deduced general equations are considered for an example of a marine ecosystem characterized by the development of four coupled processes. It is shown that the optimal prediction of these processes requires the solution of 11 systems of equations with simultaneous adaptation of prognostic estimates and the coefficients of the models to the data of observations. A numerical simulation experiment explaining the algorithm of the proposed method of modeling is considered. A conclusion is made that the application of this method in the geoinformation systems of monitoring of the environment is quite promising.