L.E. Mistrov1, V.V. Isaev2, O.V. Polyakov3
1, 3 MESC of Air Forces “N.Е. Zhukоvsky and Yu.А. Gаgаrin Air Force Academy” (Vоrоnеzh, Russia)
1 Central Branch of the Lebedev Russian State Unitary Enterprise (Vоrоnеzh, Russia)
2 ANVP “PROTEK” (Vоrоnеzh, Russia)

1 mistrov_le@mail.ru, 2 v29is@mail.ru, 3 p_oleg_65@mail.ru

The basis for synthesis of the architecture of intelligent training systems (ITS) consists of methods for synthesizing its optimal appearance and methods (algorithms) of application in the form of a set of hardware and software combined by functional solutions that provide solutions to learning-training tasks (LTT) under the control of decision makers (DM)/users. The architecture is represented as a certain set of performed domain-specific actions based on the functional purpose of ITS when solving an expanding set of technical requirements at different levels of users, the type and composition of structural elements, their functional, informational, executive and temporary interaction when performing various types of information and computational tasks. The basis of its synthesis is made up of DM solutions resulting from the analysis of objective laws of application of simulated radioelectronic objects (REO) and information about the conditions of their interaction with the external environment, consisting in the choice of goals, methods and models for solving a variety of problems by users.

Solving the problem of substantiating the appearance and methods (algorithms) of ITS application presupposes the existence/deve­lopment of methods and models for evaluating its effectiveness based on a variety of defining functions of its architecture. The architecture implements many functions based on the analysis of the content of the components of each function and the subsequent convolution of the results of the application of the functions involved in the process of solving the problem. Their finding on the basis of sequential analysis of the content of the components at the analysis stages is based on the modeling of operations to assess the specific performance indicators of each function. Also their findings taking into account the results of performance indicators ensure the determination of the performance indicator of the LTT solution based on the use of the operational-processor modeling method at the synthesis stages. At the same time, modeling is considered as a process of forming an information context that provides support for decision-making by DM on the distribution and optimization of ITS architecture functions and the training of various levels of users to manage the functioning of the REO in a variety of conditions of information interaction with the external environment by the LTT solution.

The proposed method of system modeling of the multicriterial optimization problem allows synthesizing structural and functional models of the ITS architecture. At the set-theoretical level, they describe the relationships in the three-dimensional space of application functions, control functions and structural components of the ITS architecture, which are manifested in the process of solving the LTT. Operational-processor approach modeling provides a formalized representation of the system model of the ITS architecture, which forms the information context for the development of decisions by decision makers/users on managing the information interaction of the REO organization with the external environment based on the ITS information and communication environment and, on the one hand, determines the necessary and sufficient stages of modeling, and on the other hand, reflects the functional components of decision support for various levels of users when solving the LTT for integral and partial performance indicators. A formalized representation of the functions of the ITS architecture allows synthesizing an invariant model for managing hardware and software resources when solving general and specific technical problems.

The proposed algorithms of the modeling technology, built on the basis of structural and functional models of the ITS architecture, provide structuring of the application of functions at hierarchical levels of the system model with support for the selection of control decisions based on the abstraction of the task in terms of the LTT: situation, procedure, state, attributes and trajectory. The modeling technology allows us to construct a holistic, deductively justified from the point of view of the upper hierarchical level of the ITS architecture, iteratively adapted to a given subject area, hierarchical set of models for managing the process of training users to make decisions on managing the interaction of the REO with the external environment for a deterministic set of LTT.

The implementation of the proposed system model of multi-criteria optimization of the ITS architecture allows substantiating the decisions made by users on optimal methods of managing electronic equipment in a variety of ways of information interaction with the external environment.

Mistrov L.E., Isaev V.V., Polyakov O.V. Multi-criteria optimization model of architecture of intelligent training systems. Neurocomputers. 2025. V. 27. № 5. P. 82–99. DOI: https://doi.org/10.18127/j19998554-202505-09 (in Russian)

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