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Simulation of fuzzy-logic control system based on results of customs activity

Goremykina G.I. PhD of Physics and Mathematics, Associate Professor, the Department of Applied Mathematics, the Moscow State University of Economics, Statistics and Informatics ( g_iv.05e @ mail.ru )

Mastyaeva I.N. PhD of Technical Sciences, Associate Professor, Head of the Department of Applied Mathematics, the Moscow State University of Economics, Statistics and Informatics ( imastyaeva@mesi.ru )

Journal: National Interests: Priorities and Security, #23, 2013

In the article the model of fuzzy logic control system according to the results of the customs authorities on the basis of key performance indicators is presented. In model the scheme of an indistinct conclusion across Mamdani according to expert indistinct knowledge bases is applied. Process of system development is realized in the environment of MatLab with use of a Fuzzy Logic Toolbox package and the interactive fuzzy module. Some practical recommendations on how to build this system, modeling of the system parameters are offered.


Outlining the methodology for management by objectives in line with performance results of the customs service

Goremykina G.I. Plekhanov Russian University of Economics (PRUE), Moscow, Russian Federation ( g_iv.05@mail.ru )

Gupanova Yu.E. Russian Customs Academy, Lyubertsy, Moscow Oblast, Russian Federation ( vl-rfei@mail.ru )

Journal: National Interests: Priorities and Security, #11, 2018

Subject Customs authorities should improve the customs administration mechanism, which depends on an adequate evaluation of performance results from strategically important aspects of operations. The balanced scorecard converts the mission and general strategy into specific and exact goals and indicators.
Objectives The research is to outline the methodology for management by objectives in line with performance results of customs authorities under uncertainty and professional risk exposure.
Methods The research draws upon principles of the strategic management theory, methodology of balanced scorecard, fuzzy modeling, blockchain technology.
Results We outlined the methodology for management by objectives, which is based on the balanced scorecard methodology and intellectual mathematical modeling to quantify each goal attainment progress.
Conclusions and Relevance The proposed methodology allows to determine strategic goals of the customs service and daily routine of officers at each governance level, quantify the cause-and-effect correlation and take an appropriate managerial decision. The findings may prove useful to customs authorities as a tool for management by objectives.


Modeling the Decision Support System in management of investment projects for prevention of emergency situations

Goremykina G.I. Plekhanov Russian University of Economics, Moscow, Russian Federation ( g_iv.05@mail.ru )

Konstantinova O.V. Plekhanov Russian University of Economics, Moscow, Russian Federation ( konstantinova93@yandex.ru )

Mastyaeva I.N. Plekhanov Russian University of Economics, Moscow, Russian Federation ( imastyaeva@mail.ru )

Journal: National Interests: Priorities and Security, #3, 2017

Importance A new development strategy of the EMERCOM of Russia requires a new approach set up by 2030 to shift from operational response towards risk management, prevention and elimination of large hazardous factors, risks and threats. Active investment policies of the State is one of the requirements for successful implementation of governmental programs. Growing volume of investment, formation and implementation of the effective strategy of investment development require to create and integrate scientifically proven investment management models and methods in the specific operations of the EMERCOM of Russia.
Objectives The research creates and presents computer-assisted representation of the mathematical model for systemic support of decision-making in management of investment projects for emergency prevention.
Methods The research involves the fuzzy modeling methodology.
Results We set the Decision Support System model in investment project management for prevention of emergency situations. The model is based on the fuzzy inference scheme under the Mamdani algorithm. The system has been devised in MathLab using the Fuzzy Logic Toolbox package. We performed a comparative analysis of the models, investment projects on the basis of the system and prioritized their finance.
Conclusions and Relevance The research has practical significance since the system can be used as a versatile method to manage investment projects for emergency prevention.


Modeling the risk management system in power-generating sector companies

Goremykina G.I. Moscow State University of Economics, Statistics and Informatics, Moscow, Russian Federation ( g_iv.05@mail.ru )

Mastyaeva I.N. Moscow State University of Economics, Statistics and Informatics, Moscow, Russian Federation ( imastyaeva@mesi.ru )

Fedorchuk A.A. Autonomous Non-commercial Organization UFL Organizing Committee, Moscow, Russian Federation ( anna.fedorchuk.86@mail.ru )

Journal: National Interests: Priorities and Security, #5, 2015

Importance The target-oriented and forecasting fuel and energy balance of Russia for the period until 2035 presumes advanced development of the electric-power industry for the realization of large-scale electrification of the national economy with the growth of installed power in power plants by more than 1/3 times increase and 1.6 times increase of generation of electricity. The change of functioning conditions directly impacts each electric-power industry facility. Because of this, at present, Russia is experiencing reforming of electric-power industry: of wholesale market liberalization of electric energy, implementation of the energy-saving and energy-efficiency programs, changing of tariff regulation and creation of wholesale market of power capacities. As a result, the organizations need new tools and technologies for transforming regulation market into competition market. A competition market is characterized by decision-making under condition of uncertainty. As a result, there is a need of forecasting of potential loses, and it means creating risk-management system.
     Objectives The aim of this research is the development of risk estimation model of electric energy company for constructing optimal strategy for market behavior. For achieving this goal, there were some tasks which were set up and solved, namely: different approaches to modeling risk-management system depending on quantity and quality of input data have been analyzed and compared; fuzzy-logic model of risk-management system of an electric-power company based upon key indicators and developed modeling of its parameters.
     Methods In this research, we have developed fuzzy-modeling methodology of evaluation and risks management of an electric-power company.
     Results We have constructed a model of risk management system. In the proposed model, we have used the Mamdani-Type Fuzzy Inference according to expert fuzzy knowledge basis. The development process of the system is implemented in MatLab environment using the Fuzzy Logic Toolbox package. The paper offered practical recommendations concerning construction methods of the mentioned system, and also carried out its parameters modeling.
     Conclusions and Relevance The practical significance of the research lies in the opportunity of applying the developed system as universal tool for assessing risks and creating a set of measures to minimize it.


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