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• FORMATION OF PARAMETERS OF INFORMATION SOURCES FOR NEURO-LINGUISTIC TEXT IDENTIFICATION

  К.Y. Rumyantsev , V. V. Kotenko , L.К. Khadzhieva

  173-188

  2026-07-07

  Abstract ▼

  This paper explores a method of neurolinguistic text identification aimed at analyzing and verifying information sources, including texts generated by artificial intelligence systems. Three versions of the information states of the text of Luo Guanzhong's Romance of the Three Kingdoms are analyzed: the original text and the text generated by the Gemini and GPT artificial intelligence systems. The study aims to formulate and substantiate parameters for use as identification factors in the generated text, as well as to create 3D images of neurolinguistic textual identification of information sources. The specialized software package "Neurolinguistic Text Identification Analyzer" is used, processing text data based on horizontal and vertical scanning of neurolinguistic information frames. As a result, information spectra, quantitative characteristics (information capacity, entropy, redundancy), and 3D neurolinguistic information images of neurolinguistic frames of textual information of the Chinese work are formed. A comparison of the identity levels of neurolinguistic 3D informational images of the textual information source and neurolinguistic information frames shows that the highest level of identity is observed when comparing the texts of neurolinguistic information frames with the original text, while the lowest level of identity is observed when comparing the original text with the text generated using neural networks. The obtained results demonstrate significant differences between the parameters of the neurolinguistic information frames of the original text and the parameters of the text generated by neural networks, both in terms of quantitative text characteristics and the characteristics of the neurolinguistic 3D informational images. It was found that the neurolinguistic 3D informational images of texts generated by neural networks have a smoother visual representation structure and an excellent color distribution compared to the neurolinguistic 3D images of the original text. The practical significance of this study lies in the application of an approach that allows for the identification of generated text and the verification of information sources. The obtained results open up prospects for further work and the possibility of creating programs capable of detecting the presence of text generation

• MULTI-AGENT INTELLIGENT SYSTEM FOR CONTROL OF PARKING SPACES IN CITY INFRASTRUCTURE

  I. А. Pshenokova, К.C. Bzhikhatlov, М.А. Kanokova

  2025-04-27

  Abstract ▼

  With the growing number of cars and limited space, many cities are realizing the importance of implementing
  intelligent parking systems to improve urban mobility and convenience for drivers. The level of
  implementation of intelligent parking based on various technological solutions is growing, but to achieve
  maximum efficiency, it is necessary to continue to develop technologies, integrate them with other systems
  and take into account the needs of users. The purpose of the study is to develop a multi-agent intelligent
  system for monitoring and managing parking space reservations in the city parking network. The architecture
  of a multi-agent intelligent parking management system has been developed, which provides automatic
  access control to parking spaces taking into account the wishes of parking lot owners, driver orders, the traffic
  situation in the city and safety requirements. The main element of the developed system is parking, which
  is represented by a set of parking spaces equipped with automated parking space management systems (parking
  attendants), a communication system and data collection tools (surveillance camera and weather stations).
  Parking spaces and parking attendants are managed by an intelligent control system based on multiagent
  neurocognitive architectures. A prototype of a hardware and software complex of a multi-agent intelligent
  parking space management system has been developed in the form of a client-server architecture.
  The server is responsible for collecting, processing, storing data and managing automated parking attendants.
  Two types of clients are connected to the server - a mobile application of the administrator and the
  driver. The administrator has the ability to manage parking (set fixed prices or use server recommendations,
  book parking spaces for employees) and view statistics (current load, parking statistics, data on accepted
  payments, parking work forecast, recommendations). The driver has the ability to view the status of parking
  in the area of interest (number of free spaces, waiting time for a free space, cost, recommendations for the
  most convenient parking) and book a parking space with the ability to pay online

• INTELLIGENT RECOMMENDER SYSTEM FOR SPATIAL ANALYSIS

  S.L. Belyakov, А. V. Bozhenyuk, N. А. Golova, К.S. Yavorchuk, I.N. Rosenberg

  14-26

  2025-07-31

  Abstract ▼

  The work is devoted to the analysis of mechanisms of formation of recommendations and
  evaluation of the user's reaction to them in the interactive mode of work with the geoinformation
  system. One of the important areas of application of recommender systems is the search and decision-
  making in spatial situations. A peculiarity of this class of problems is the uncertainty of task definition and ambiguity of decision evaluation. Users are often faced with problems that do not
  have a clear formulation. To try to solve them, it is necessary not only to designate the direction of
  solution search, but also to find an adequate sequence of tasks with clearly formulated input and
  output data. Recommendations in such cases are designed in a dialogue with the user-analyst to
  develop a strategy for finding solutions. In this paper we study a smart recommendation system
  using the experience of dialog interaction. We propose a model of adaptation to the mental image
  of the problem, which builds the user, taking into account the levels of situational awareness and
  cognitive load. The peculiarity of the model is the use of visual cartographic objects, which are
  indicators of the state of the mental image. A recommendation is represented by a set of objects
  that are introduced into the field of cartographic analysis. This implicitly induces a certain semantic
  direction of increasing situational awareness. A criterion of satisfaction with the recommendation
  is suggested. A diagram of recommender system states, which describes the selection of context,
  adequate to the problem being solved, is given. The context is understood as an information
  object, capable of providing program functions and data for solving problems of a limited class.
  A sequence of contexts in an analysis session is considered as a precedent of experience. Indicators
  of trend, tendency and rhythm are proposed for possible chains of contexts. The degree of
  semantic proximity of precedents to the current course of search for a solution is estimated by
  these indicators. Their use will increase the speed of adaptation.

• INTELLIGENT RECOMMENDER SYSTEM FOR SPATIAL ANALYSIS

  S.L. Belyakov, А.V. Bozhenyuk, N.А. Golova, К.S. Yavorchuk, I.N. Rosenberg

  14-26

  2025-07-30

  Abstract ▼

  The work is devoted to the analysis of mechanisms of formation of recommendations and
  evaluation of the user's reaction to them in the interactive mode of work with the geoinformation
  system. One of the important areas of application of recommender systems is the search and decision-
  making in spatial situations. A peculiarity of this class of problems is the uncertainty of task definition and ambiguity of decision evaluation. Users are often faced with problems that do not
  have a clear formulation. To try to solve them, it is necessary not only to designate the direction of
  solution search, but also to find an adequate sequence of tasks with clearly formulated input and
  output data. Recommendations in such cases are designed in a dialogue with the user-analyst to
  develop a strategy for finding solutions. In this paper we study a smart recommendation system
  using the experience of dialog interaction. We propose a model of adaptation to the mental image
  of the problem, which builds the user, taking into account the levels of situational awareness and
  cognitive load. The peculiarity of the model is the use of visual cartographic objects, which are
  indicators of the state of the mental image. A recommendation is represented by a set of objects
  that are introduced into the field of cartographic analysis. This implicitly induces a certain semantic
  direction of increasing situational awareness. A criterion of satisfaction with the recommendation
  is suggested. A diagram of recommender system states, which describes the selection of context,
  adequate to the problem being solved, is given. The context is understood as an information
  object, capable of providing program functions and data for solving problems of a limited class.
  A sequence of contexts in an analysis session is considered as a precedent of experience. Indicators
  of trend, tendency and rhythm are proposed for possible chains of contexts. The degree of
  semantic proximity of precedents to the current course of search for a solution is estimated by
  these indicators. Their use will increase the speed of adaptation

• KNOWLEDGE FOR ARGUMENTATION IN COMPARISON OF SPATIAL SITUATIONS

  S.L. Belyakov, N.А. Golova, К.S. Yavorchuk, I. N. Rosenberg

  2022-05-26

  Abstract ▼

  The traditionally used way to assess the quality of the solution proposed by an intelligent
  system is to explain the course of logical inference. Knowledge about reasoning is used to argue
  the choice of a solution option. The sequence of applied rules, the facts used and the confirmed
  hypotheses are considered arguments that should convince the user of the validity of the formed
  conclusion. The disadvantage of this method of explanation is that it reflects a formally correct,
  but devoid of semantic content, course of reasoning. The argumentation of the solution obtained is
  based on the tracing protocol, which is essentially no different from debugging information when
  tracing programs. The argumentation in this case is far from the meaning of the situation. The
  meaning is understood as a given set of transformations of the situation that preserve the immutability
  of its perception by a human analyst. Knowledge about the semantic content of situations
  should be presented in a special fashion. In this paper, we consider a representation containing a
  precent and its permissible transformations. In this form, spatial situations in geoinformation systems
  are described. For argumentation, it is proposed to use special relations between images of
  situations. The concept of the area of applicability of the image is introduced. The mutual arrangement of the spatial-temporal and semantic shell of images and the areas of their applicability
  is considered as a carrier of the relationship. Information about relationships is extracted from the
  structure of the cartographic database. The relations of inheritance, aggregation, composition,
  generalization and association of classes of objects are considered. Knowledge for argumentation
  is provided by the rules for determining the reliability index of expert conclusion for individual
  relationships and their combinations. A method of automatic rule generation is proposed.
  The relations for comparison of levels of reliability of rules are given.

• INTELLIGENT SUBSYSTEM FOR DECISION SUPPORT BASED ON BIOLOGICALLY PLAUSIBLE ALGORITHMS FOR SELF-ORGANIZATION

  E.V. Kuliev , M.P. Krivenko, М.М. Semenova, S. V. Ignatieva

  2021-11-14

  Abstract ▼

  The article discusses the basic concepts and definitions of decision support systems based
  on self-organization. Decision Support Systems refers to a range of interactive computer systems
  that help to use data, models, and knowledge to solve semi-structured, unstructured, or unstructured
  problems. The diagram of the basic structure of the decision support system is shown and
  described. Three main components of Decision Support Systems are considered, and a case is
  described when the fourth component of a decision support system - a knowledge-based management
  system - can be applied. The article offers a description of an intelligent decision support
  system. Examples of specialized intelligent decision support systems include intelligent marketing
  decision support systems and medical diagnostics systems, flexible manufacturing systems. The
  problems associated with making optimal decisions occupy an important place in computer-aided
  design and require improving methods and means of supporting optimal design processes at various
  stages. Self-organization algorithms inspired by wildlife are considered. Bioinspired algorithms
  are a representative class of self-organization algorithms. Bio-inspired computing mimics
  nature and uses the underlying concepts and behavior of these systems to solve complex problems.
  The article describes the algorithm for bats. An experimental analysis of the process of applying
  the self-organization algorithm in decision-making systems is carried out.

• TRANSFORMING THE DECISION-MAKING EXPERIENCE

  S. L. Belyakov, M. L. Belyakova, S.A. Zubkov, N.A. Golova, K.S. Yavorchuk

  2021-01-19

  Abstract ▼

  The problem of transferring the experience of decision-making in situational analysis using
  geoinformation systems is considered. The need for intellectual support from the geoinformation
  system is due to the fact that spatial objects and connections of the real world are extremely dynamic.
  Under these conditions, it is not possible to apply analytical models of processes and phenomena
  due to the incompleteness and inconsistency of the information describing them. Statistical
  models depend on a large number of factors, which vary as the geographical location of the
  situation changes. An alternative is to use the experience of experts who are able to make effective
  decisions in local spatial situations. The lack of control over the reuse of experience is a problem.
  The knowledge gained in developing solutions in one locality can lead to inadequate solutions in
  another locality. The experience of solving a problem in the same area loses its significance over
  time. In this paper, we propose a representation of knowledge in the form of an image consisting
  of a center and acceptable transformations of the center. Image transformation functions that
  perform knowledge transfer are introduced. The properties of transformation functions that carry
  procedural knowledge about the images of situations are analyzed. The use of the identified properties
  for the formation of a test plan for software transformation procedures is considered. Thecriteria for successful transformation are studied. The optimization problem of finding the best
  transformation function in the GIS knowledge base is formulated. A generalized method of transforming
  experience is proposed. An example of the synthesis of transformation methods for selecting
  an operational call center is given. The image of the situation of making a decision about
  choosing a land plot for a service center is transformed into the specified area on the GIS map.

• IMPLICIT THREATS IDENTIFICATION BASED ON ANALYSIS OF USER ACTIVITY ON THE INTERNET SPACE

  V. V. Bova , D. Y. Zaporozhets, Y.A. Kravchenko , E. V. Kuliev , V. V. Kureichik , N. A. Lyz

  2020-10-11

  Abstract ▼

  The article is devoted to the problem of identifying implicit information threats of a user's
  search activity in the internet space based on an analysis of his activity in the course of this interaction.
  The use of knowledge stored in the Internet space for the implementation of criminal intentions
  poses a threat to the whole society. Identifying malicious intent in the users’ actions of the
  global information network is not always a trivial task. The proven technologies for analyzing the
  context of user interests fail in the case of cautious and competent actions of attackers who do not
  explicitly demonstrate the goal they are pursuing. The paper analyzes the threats associated with
  certain scenarios for the implementation of search procedures that manifest themselves in search
  activities. Criteria of inefficient and effective search scenarios estimation are described. Among
  the signs indicating the possibility of a threat, the following main ones are highlighted: avoiding
  solving the problem in aimless navigation or attractive resources, superficial search, lack of
  meaningful immersion in solving the search problem, and chaotic actions during the search.
  To determine the presence of adverse signs, a system of indicators is built. The features of an effective
  scenario for organizing a search in the Internet space are formulated, options for the presence
  of implicit threats for a similar situation are described.An approach for identification the
  described threats is presented taking into account the specified criteria for evaluating various
  scenarios of user behavior in the global information space. A machine learning algorithm has
  been developed to identify problem scenarios by comparing with key behavioral patterns. The
  software implementation of the subsystem for identifying information threats has been created,
  experimental studies have been conducted to confirm the effectiveness of the subsystem. Experimental
  studies were carried out on the basis of processing open data from social networks, as well
  as using analysis of user search activity in the university corporate information environment.

• CONCEPTUAL MODEL OF FACTORS INFLUENCING THE EFFICIENCY OF GAS PREPARATION AND SEPARATION PROCESS

  А. V. Martirosyan , D. V. Romashin

  241-249

  2026-09-10

  Abstract ▼

  The paper presents the concept of adaptive control in natural gas separation. The control systems used in practice are usually based on fixed control algorithms and do not consider dynamic changes in physical, technical and operational parameters, which leads to a decrease in separation quality and an increase in energy consumption. The article describes the approach of combining system analysis, modeling and the Pareto method. This paper presents a concept for adaptive control in natural gas separation. Control systems used in practice are typically based on fixed control algorithms and do not account for dynamic changes in physical, technical, and operational parameters, which leads to reduced separation quality and increased energy costs. This paper describes an approach combining systems analysis and the Pareto method. The aim of this paper is to develop a concept for adaptive control of the natural gas treatment process based on systems analysis. Recent studies demonstrate that data-driven methods enable more precise parameter adjustment, better responsiveness to raw-gas fluctuations and improved impurity removal efficiency. To achieve this goal, this paper addresses the challenges of identifying and classifying factors affecting the quality and efficiency of gas separation, as well as integrating their relationships within a unified conceptual control model. Particular attention is paid to the impact of precise control of key parameters, such as pressure, temperature, and flow rate, on the efficiency of these processes. An analysis of recent research demonstrates the growing use of neural networks and machine learning models in gas purification for predictive control, anomaly detection, and optimization of operating parameters. A comparative evaluation of classic PID controllers, fuzzy, adaptive, and neural control methods confirms the advantages of intelligent control in terms of stability, adaptability, and energy efficiency. The main result of this study is the substantiation of key factors determining separation efficiency, among which pressure, temperature, and gas flow rate have the greatest impact. The resulting model forms a methodological basis for the development of intelligent and adaptive control systems for gas purification processes.