articles
| Modern economic conditions are characterized by a high degree of uncertainty and complexity, which is difficult to formalize. Fuzzy cognitive maps make it possible to solve this problem – to cope with complexity, but when cognitive maps are built on the basis of expert opinions, this sometimes causes distrust due to the subjectivity of the judgments of individual specialists and doubts about compliance with the examination procedure. Therefore, the task of developing analytical tools to increase the awareness of decision makers about the real state of affairs in the organization and in the external environment is relevant, because contributes to the growth of their efficiency. The article proposes and tests a procedure for automated construction of a cause-and-effect diagram using statistical methods, as well as methods and models of machine learning. With the help of modern methods of topic modeling, key topics (concepts) are identified in the area under consideration for the considered period of time. The Doc2Vec model is then used to derive a fixed length numeric vector from the identified topics. The Granger test is then used to establish the possibility of a causal relationship between the topics found. The constructed cause-and-effect diagram allows you to describe the current situation and understand the key concepts of the area under consideration. According to the Russian media for 20 years (from 2002 to 2021), a cause-and-effect diagram was built that reflects the problems of strategic management in Russia. The analysis of the diagram made it possible to conclude that the topic of Russian projects is the most significant in the area under consideration Continue... | |
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№ 2(104)
31 march 2023 year
Rubric: Data protection Authors: Puchkov A., Prokimnov N., Shirokov S., Sokolov A. M. |
The results of studies are presented, the purpose of which was to develop an algorithm for identifying information security threats in distributed multiservice networks that provide information interaction of regional government bodies, as well as their communication with the population of the region. The relevance of the research topic is due to a significant increase in various types of cyber attacks on the computer networks of public authorities and the need to increase the level of security of these networks by intellectualizing methods for combating information security threats. The algorithm is based on the use of machine learning methods to analyze incoming traffic in order to identify events that affect the state of information security of public authorities. The algorithm provides for input traffic preprocessing, as a result of which a set of images (signatures) obtained from Wasm binary files is formed, and then the image classifier is launched. It contains a sequential inclusion of deep neural networks – a convolutional neural network for signature classification and a recurrent network that processes the sequences obtained at the output of the convolutional network. Features of the formation of signatures in the proposed algorithm, as well as sequences at the input to the recurrent network, make it possible to obtain the resulting assessment of information security, taking into account the history of its current state. The output of the recurrent network is aggregated with the result of comparing the actual signatures with those available in the database. The aggregation is performed by the fuzzy inference system of the second type, using the implication according to the Mamdani algorithm, which generates the final assessment of information security threats. Software was developed that implements the proposed algorithm, experiments were carried out on a synthetic data set, which showed the efficiency of the algorithm, confirmed the feasibility of its further improvement. Continue... |
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№ 2(104)
31 march 2023 year
Rubric: Researching of processes and systems Authors: Chumakova E., Gasparian M., Korneev D., Makhov I. |
The article is devoted to the issues of controlling the operational risks of a credit institution arising in the process of using IT technologies. Among banking risks, operational risk occupies a special place, primarily due to the fact, that it affects various areas of banking activity and is difficult to separate from other types of risk. Operational risks arise, among other things, as a result of downtime or incorrect operation of technical systems and equipment. Due to the constant growth in the degree of automation of banking business processes, new IT risk groups are emerging that can have a significant impact on the activities of a credit institution. The aim of the work is to create an artificial neural network using the high-level Keras library in Python, which automatically controls the level of criticality of the IT risk that has arisen. In the article, based on the analysis of risk events associated with the use of IT technologies, the data flows entering the input of the neural network is identified and its structure is determined. The paper also presents the results of training a neural network created by the authors based on the generated data sets. The use of intelligent methods for assessing the level of criticality of operational IT risk allows you to quickly take measures to minimize the consequences, and thus reduce direct and indirect losses. In connection with the above, the automation of operational risk management based on the use of neural network technologies is currently one of the most urgent tasks for credit institutions. The results obtained are new and can be used by credit institutions in the process of building automated systems for monitoring and managing operational risks. Continue... |
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№ 2(104)
31 march 2023 year
Rubric: Researching of processes and systems Authors: Rozhkov V., Butrimov S., Fedotov V., Krutikov K. |
The article analyzes the operation of thyristor automatic switching devices for uninterruptible power supply units of nuclear power plants. They are part of the emergency power supply system for auxiliary electrical equipment with a rated voltage of 0.4 kV. In such a reliable power supply system for especially responsible consumers, alternative networks and backup sources are necessarily used. Typically, groups of consumers for auxiliary needs of nuclear power plants are powered from the inverter network, so that in the event of a shutdown of the backup bypass network, these loads continue to be powered by the uninterruptible power supply unit. It incorporates a charger – a controlled rectifier, a battery pack and a transistor inverter. The transition from one network to another in any direction must be “shockless” in order to avoid the operation of the protections of uninterruptible power units and other electrical protections of the reliable power supply system. If there are failures in the algorithms or their irrational organization, the processes of transition between networks may be accompanied by a violation of uninterrupted power supply or phase-to-phase short circuits. A structural simulation model has been created in the MatLab computer mathematics system for testing transition algorithms for various phase shifts of networks and transition directions. The algorithm of transition between networks for uninterruptible power units of one of the manufacturing companies that supplied equipment to nuclear power plants was analyzed. A safer optimal algorithm for controlling network switching with phase-by-phase control of the current drop in the disconnected network is proposed. The proposals are supported by the results of computer simulations. Continue... |
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№ 2(104)
31 march 2023 year
Rubric: Mathematical methods of economic Authors: Tindova M., Ledneva O. |
In this paper, the authors conduct a comparative analysis of instrumental methods used in modeling stochastic processes, namely, component analysis of time series, fractal modeling and modeling using p-adic mathematics. As an object of study, the authors chose the dynamics of the MICEX index. At the first step of the work, the authors carry out a detailed component analysis of the time series, which made it possible to identify the main development trend in the form of a quadratic function; periodic fluctuations with a period of six levels and a cyclical component describing fluctuations in the world economy with a period of fifty-five levels. At the second step of the work, the authors simulate the dynamics of the MICEX index using a fractal theory based on the self-similarity of the development of the economic process, which showed the ergodicity of the series under study with a stable influence of only the last twenty-four levels. The third step of the work was the p-adic modeling of the patterns existing in the series under study, which allowed the authors to reduce the model error to 6.8%. As a result of the work, a forecast of the dynamics of the MICEX exchange rate at four levels is presented, presented in three scenarios: optimistic, realistic and pessimistic. As conclusions of the work, an analysis was made of the possibility of using the considered methods for multiple, medium and long-term forecasts; the complexity of the methods and the need to use special software products are evaluated. Continue... |
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№ 3(105)
16 june 2023 year
Rubric: Performance management Authors: Halin V., Chernova G., Kalayda S., Yurkov A. |
Solving the problems of effective business management is associated with a variety of current goals facing the same and, by implication, requires the construction of appropriate models of efficient business. The article presents two problems of doing business which, apart from their common target being an improvement of business efficiency, have different current goals. The creation or development of any business involves the construction of a specific business plan for it, including a list of those areas of business development, the implementation of which will increase its efficiency. The first problem considered in the article is related to the phased implementation of all areas of efficiency improvement in order to ultimately obtain the greatest efficiency of their realization. The second one solves the problem of increasing efficiency by partially implementing efficiency improvement directions from the initial list, taking into account certain limitations, for example, in conditions of limited company resources. For the construction of models which would meet the problems set, an efficiency criterion is substantiated and proposed in the article, and Algorithms 1 and 2 are developed which made it possible to build the efficient business models which take into account the difference in its current goals. The authors have developed a multi-stage Algorithm 1 for the generation of individual sets of areas for improvement of efficiency to be used to solve the tasks at hand. Algorithm 2 implemented at each stage of Algorithm 1 has been developed by the authors by using the Pareto optimality method but supplemented by taking into account the features and objectives of the current tasks set for the business. The use of such algorithms has made it possible to build efficient business models enabling not only to obtain an economic effect inherent to each efficiency improvement area, but also to ensure additional growth thereof driven by the properties of the developed algorithms. Continue... |
