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Abstract. The article considers the features of the modern machine-building complex of Bryansk region. The authors have developed a component classifier of an industrial enterprise internal environment; have formed the machine-building enterprise fuzzy model describing its internal environment factor relationship. The main result of the model made was forming a confidence interval that describes the mutual influence degree of the internal environment factors of a machine-building enterprise.

The current state of modeling regional social and economic systems cannot still be defined as an effective tool for developing regional policies in the Russian Federation. The article provides an algorithm for modeling a regional social and economic system for the needs of the information advisory system being developed. The authors determined the functional significance of the mathematical modeling block of the regional social and economic system in the developed information advisory system; its interaction with other components of the program is described.The authors developed an algorithm that proves feasibility of applying the specific mathematical function to describe trends in the development of indicators for the forecast of the social and economic development of the RF region in the information advisory system being developed.The generated algorithm provides for the possibility of using single- or multifactor regression to form a mathematical dependence. It is shown that the result of mathematical modeling in the advisory system is the formation of a list of indicators assigned to the executive state government bodies or subdivisions of the regional government for which the information advisory system forms an assessment of the values оf indicators for the near future. Using the principle of materiality, the program forms recommendations regarding the need for management impact on the analyzed indicators. The article using the example of the Bryansk region presents the experience of using multiple regression for modeling values of the sample indicator of the development of the regional social and economic system "Investments in fixed assets". As initial data, the departmental expenditure structure of the Bryansk region for the departments of economic development and construction and architecture for 2011-2019 was used. In the program module Statistica, the corresponding regression equations were formed, and then the model was evaluated for reliability. The results of regression analysis for the estimated indicator are also given. The article provides the conclusion stating that the use of multifactor correlation-regression analysis for modeling a regional social and economic system based on the Bryansk region data makes it possible to expand the capabilities of the information advisory system being developed.

This article discusses an approach to building systems based on the knowledge with ability to extend their own domain knowledge through obtaining information in the Internet. In that approach proposed to use infinity loop in which the system automatically learns to find good quality documents within a knowledge area represented in Internet using ontology and expert preferences and on next step extend this ontology by extracting knowledge from retrieved documents. Such approach would let to create a system capable of continuously increase their own knowledge by exploring documents in the Internet and solve problems using current state of the knowledge area.

An approach to determining the systemic increase in the management efficiency of the Regional Socio-Economic System (RSES) control system is presented, which is based on the emergence property. It is shown that the cumulative synergistic effect is accumulated due to both the mutual positive influence of the RF National Project indicators on each other, and due to introducing the proposed methodology for managing the RSES, which allows timely adjusting the managerial impact on the RSES, which will give the opportunity to achieve the declared targets of the RF National Projects at the stated time.