Development of Control Models of Non-Stationary Systems in Limited Conditions
Abstract
This study examines the issue of optimization of management models, which mainly focuses on the prediction of economic indicators and management based on neural models. Non-stationary processes, reflecting technological, economic, social, biological, physical phenomena, are characterized by quantitative and qualitative characteristics, which are characterized by abrupt, evolving development and regulation of parameters over time. Modeling of non-stationary processes in the general case can be carried out using traditional mathematical methods, but today a promising area of research is the use of modern methods of intelligent data processing, one of the brightest representatives of which are neural network technologies. Therefore, it is important to improve management models to implement the above tasks.