Semantics and Selforganization in Nanoscale Physics

Each complex system interacts with environment, which is changing, and the live of complex system depends on the adaptational possibility of our system. The problem of simulation of condition of guarantee to the adaptational maximum is investigating. It is suggested that the behavior of system with n variables is given to an approximation of m intersecting manifolds, n > m. If the system is considered as a multidimentional generator whereat least a part of variable interact with environment's variables, and if the objective of system is to decrease the functional of discoordination between them, the system control unit has two instruments of influence of the system. First, this is the tuning - the change of underdeterminated coefficients in the structure of the differential equations of system taking account that more is these coefficients the more accurate are the responses of the system to the change of environment. Second, this is the learning - the imposition of new restriction on the systems behavior. The amount of arbitrary coefficients in the structure, of equivalent equations is changing in the process of learning, of consecutive imposition of new and new restrictions on the system behavior. In the systems with the number of variables more than six the amount of arbitrary coefficients increase first and then going through the maximum begin to decrease. This phenomenon permits to explain the processes of growth, complication and death of a system. The existence of adaptational maximum phenomenon is proved by numerous biological, economical and physical-technical systems. We use the linguo-combinatorial method of investigation of the poorly formalized complex system, then we use the key words for creation of equivalent equations. The study of adaptational phenomenon in complex systems permits to increase the adaptational possibility in different systems. This paper discusses utilization of linguo-combinatorial simulation approach for complex systems modeling. When dealing with complex systems one has to consider that conditions and environment are not fully determined. In the course of this paper it is discussed how a poorly formalized system can be efficiently represented and modeled by combinatorial simulation.