Mathematical models of stationary macrosystem states

A general approach is proposed to design of mathematical models of stationary states for systems whose properties are stochastically deterministic (macrosystems). Three types of macrosystems are considered which implement Fermi, Einstein, and Boltzmann statistics, modified in that the potential for recognition of a priori information is extended. The properties of these classes of macrosystem models are studied. A general structure of mathematical models describing stationary states is developed,, the relationship with the existing models is established, functioning algorithms are proposed, and their convergence is studied.