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• 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

• MULTI-AGENT ALGORITHM FOR COLLECTING DATA FROM WEATHER STATION FOR FORECASTING PRODUCTIVITY AND CROPS CONDITION

  I.А. Pshenokova, К.C. Bzhikhatlov, А. А. Unagasov, М.А. Abazokov

  91-101

  2022-04-21

  Abstract ▼

  The weather affects the productivity and condition of crops, the requirements for the quantity
  and quality of fertilizers, as well as preventive measures to prevent diseases. Bad weather can
  affect the quality of products during transportation and storage, and hence the germination of
  seeds and planting material. Various intelligent monitoring systems are now widely used in agriculture,
  which include satellite monitoring and weather stations. In this case, the choice of a
  method for analyzing the received data and intelligent systems for their processing for predictive
  forecasting plays a fundamental role. The purpose of this study is to develop an intellectual system
  for predicting the state of the crop based on data from a weather station. A multi-agent algorithm
  for predicting the state of crops according to data from a weather station based on the selforganization
  of neurocognitive architecture was developed in this study. The description of the
  block diagram of the weather station and its sensors is given. A program algorithm has been developed
  for collecting and processing data from weather station sensors. As a result of processing,
  data on air and soil temperature, air and soil humidity, wind speed and direction, precipitation
  amount and the sum of active temperatures are sent to the intelligent decision-making system. A
  system for constructing cause-and-effect relationships is described. This system can make recommendations
  or forecasts on the condition of the crop and on the likelihood of diseases and pests in
  controlled crops.

• DEVELOPMENT OF INTELLIGENT INTEGRATED SYSTEM FOR "SMART" AGRICULTURAL PRODUCTION

  Z.V. Nagoev, V. М. Shuganov, А.U. Zammoev, К. C. Bzhikhatlov, Z.Z. Ivanov

  2022-04-21

  Abstract ▼

  The production of agricultural goods is currently associated with the use of digital technologies,
  elements of precision farming, automation and robotization of agriculture. These technologies
  make it possible to carry out continuous monitoring, carry out timely processing, improve the
  efficiency of production and use of resources. The need for the integrated use of digital technologies
  and artificial intelligence and the creation of intelligent integrated systems for agricultural
  production is noted. Studies show that IT-technologies are actively used in field farming when
  growing grain crops. The main crop in the production of breeding, seed and commercial grain in
  the Kabardino-Balkarian Republic is corn, so it is assumed that the intelligent system of the "smart
  field" should be developed initially for this particular crop, and then, with some modifications,
  used for the production of any crop products – other types of grain, vegetables, fruits, grapes and
  gourds. It allows you to reduce human participation at some stages of production by automating
  the process and controlling it through various "smart" devices. The operation of the "smart field"
  system is based on the use of a variety of sensors, including those installed on mobile equipment
  (ground and air manned and unmanned vehicles, space satellites) and portable portable devices to
  obtain operational data on the state of fields and crops. This allows: – analyze the readiness of
  agricultural land for sowing, monitor the progress of plant vegetation in order to effectively and
  efficiently plan agrotechnical measures (chemical protection against pests and diseases, fertilizing,
  irrigation, etc.); – predict production efficiency indicators (total gross harvest, yield per hectare), as well as timely identify production risks (appearance of pests, plant diseases, soil salinity,
  etc.). – make effective decisions on managing the use of resources of agricultural enterprises. With
  the use of "smart" devices, it became possible to introduce the so-called. "precision farming" to
  manage crop productivity, taking into account changes in the plant habitat. Ultimately, this makes
  it possible to solve two main tasks of agricultural producers - increasing yields and reducing
  costs. The authors have developed the concept of an intelligent integrated system "Smart Field" for
  the production of corn grain using advanced robotic systems and complexes. The architecture of
  the "Smart Field" system for the production of seed and commercial corn is presented, which can
  be adapted with minor modifications for the production of other crop products.

• BIOINSPIRED SIMULATION METHOD FOR SCHEDULING OF PARALLEL FLOWS APPLICATIONS IN GRID-SYSTEMS

  D.Y. Kravchenko, Y.A. Kravchenko, V. V. Kureichik, A.E. Saak

  2020-07-20

  Abstract ▼

  The article is devoted to solving the problem of parallel requests scheduling flows in spatially
  distributed computing systems. The relevance of the task is justified by a significant increase in
  the demand for the distributed computing paradigm in the conditions of information overflow and
  uncertainty. The article discusses the problems of scheduling user requests that require severalprocessors at the same time, which goes beyond the classical theory of schedules. The aspects of
  the efficiency of using heuristic algorithms for scheduling planar resources are analyzed. The
  reasons for their insufficiency are determined both in terms of effectiveness and empirical approaches.
  The paper proposes to solve the problem of scheduling parallel applications based on
  the integrated application of intelligent agents coalition and an event simulation model. It is proposed
  to classify incoming applications on the basis of using a modified bio-inspired optimization
  method for cuckoo search. The joint use of a coalition of intelligent agents and a bio-inspired
  method will allow for unprecedented parallelism of calculations, and the subsequent determination
  of the processing classified applications ways on the basis of a simulation model will allow us
  to form sets of alternative solutions to speed up problem solving and optimize the distribution of
  available computing resources depending on the sets of incoming applications. To evaluate the
  effectiveness of the proposed approach, a software product was developed and experiments were
  conducted with a different number of incoming applications. Each incoming application has a
  certain set of attributes, which is a vector of the application characteristics. The degree of the
  application similarity feature vector and the vertex reference feature vector in the distributing
  simulation model is a classification criterion for the application. To improve the quality of the dispatch
  process, new procedures for duplicating unclassified applications have been introduced, which
  allow intensifying the search for matches in feature vectors. It also provides backup dispatching trajectories
  necessary for processing precedents for the appearance of applications with absolute priority
  at the inputs. The quantitative estimates obtained demonstrate time savings in solving problems of
  relatively large dimension (from 500,000 vertices) of at least 10%. The time complexity in the considered
  examples was O (n 2). The described studies have a high level of theoretical and practical significance
  and are directly related to the solution of classical problems of artificial intelligence
  aimed at finding hidden dependencies and patterns on a large set of big data.

• APPROACH TO TRAFFIC MANAGEMENT BASED ON THE IEC 61499 STANDARD

  D. M. Elkin , V. V. Vyatkin

  2021-01-19

  Abstract ▼

  The number of vehicles on public roads is constantly increasing, and the development of road
  infrastructure is proceeding at a slow pace, and not high-quality transport management entails an
  increase in transportation costs, an increase in accidents, noise levels, and environmental pollution.
  As a consequence, there is a need to apply advanced algorithms and approaches to transport management
  in order to maximize the use of the existing road network and increase road capacity. In the
  course of recent studies, it has been revealed that adaptive approaches to traffic management are
  most effective on sections of the road network with high traffic intensity and variability. The essence
  of the approaches to adaptive management used today is that they are based on the analysis of traffic
  congestion and change the phases of traffic light operation depending on the received data in real
  time .. Adaptive traffic management shows much better results compared to tight control , significantly
  reduces transport delays, travel time and emissions of harmful substances into the atmosphere,
  therefore, modern researchers are developing new and improving existing approaches and algorithms
  for adaptive transport control. For example, traffic management approaches based on the
  concept of IoT and the use of cloud computing are actively developing. The concepts of applying the
  agent-based approach to adaptive control are also being developed. The paper proposes a method
  for managing traffic flows and automating road infrastructure using an agent-based approach. The
  proposed approach includes distributed management of various elements of the road network and
  their direct interconnection with each other. To implement this concept, the open standard of distributed
  control and automation systems IEC 61499 was used, and to test the feasibility of implementation,
  several models of traffic intersections were used, one of which was created on the basis of real
  data and SUMO - a microscopic and continuous traffic simulation package.