CHARACTERISTICS OF A RANDOM PROCESS IN PROBLEMS OF COMPUTER MODELING AND ENTROPY ANALYSIS OF SYSTEMS 

Aleksandr V. Poltavskiy, Doctor of technical sciences, leading researcher, V. A. Trapeznikov Institute of Management Problems of the Russian Academy of Sciences (65 Profsoyuznaya street, Moscow, Russia), E-mail: avp57avp@yandex.ru
Andrey A. Tyugashev, Doctor of technical sciences, associate professor, professor of sub-department of computer technology, Samara State Technical University (244 Molodogvardeyskaya street, Samara, Russia), E-mail: tau797@mail.ru
Nikolay K. Yurkov, Doctor of technical sciences, professor, the honoured worker of science of the Russian Federation, head of sub-department of radio equipment design and production, Penza State University (40 Krasnaya street, Penza, Russia), E-mail: yurkov_NK@mail.ru 

658.562 

10.21685/2307-4205-2021-3-5 

Background. The present time is characterized by the intensive development of the means of informatization of society, the widespread introduction of digital systems and computer technologies with support for managerial decision-making. In these main directions, the development of a variety of information models and software tools is associated with the study, modeling of various systems taking into account random disturbances. Accounting for random factors is necessary today and extends to multi-level, multi-connected and hierarchical systems. Materials and methods. The article presents an approach to teaching information modeling of a random process and one of the aspects in applied problems of developing new knowledge (thesaurus), primarily for multifunctional information and measurement control systems (IIUS) and multi-channel object positioning systems. Results and conclusions. The given provisions can be useful in teaching students of the natural science and mathematical profile the basic provisions in probability theory, for the design and construction of information and analytical systems (IAS) of information modeling. 

geoinformation system, Wiener process, probability density, Markov process, information entropy