ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 2. Vol. 25. 2019

DOI: 10.17587/it.25.107-116

A. B. Barsky, D. Sc., Professor, e-mail: arkbarsk@mail.ru, D. I. Melnik, Ph. D., Senior Researcher, e-mail: mdi_dim@mail.ru, A. V. Reshetnikov, Ph. D., Associate Professor, e-mail: andyresh2014@yandex.ru, Scientific Research Institute (Moscow) Central Research Institute VVKO, Ministry of Defense of Russia

Neural Network Methods of Quality Management during the Modernization and Development of Complex Systems in the Context of Financial and Technological Constraints

A complex queuing system is considered, as a complex of interacting tools that solve a common problem in accordance with the objective function and with the required values of the service parameters. The objective function displays the specific purpose of a complex system with the required values of the main service parameters in accordance with the terms of reference for its development. Concerning the values of these parameters, the condition of their maximization or minimization can be specified. Modernization of the system counteracts two main processes of degradation: "physical" aging and moral aging. However, during the operation of a complex system, structural defects of facilities and their controls, as well as software errors, may be revealed. In the general case, complex systems have a centralized management body and form a centralized network, the nodes of which display individual objects. The concept of object rating is introduced, which reflects the degree of its participation in providing high quality of a complex system. For each type of objects, using the suggestions of experts, a rating system is built on the logical neural network. With its help, the monitoring results determine the current rating of the object. If the rating has fallen below acceptable, the object claims to be repaired, replaced, upgraded, etc. In the conditions of financial and technological constraints, the optimal decision on many objects is made on the basis of the scale of their importance.
Keywords: complex system, object, degradation, object rating, logical neural network, rating system, scale of importance

P. 107–116

To the contents