Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-65-78
A. Bobryakov, V. Borisov, A. Misnik, S. Prakapenka
The article is devoted to the issues of modeling and designing information-analytical processes corresponding to the production and technological processes at the enterprise. In the modern conditions of the functioning of the market, the enterprise faces important tasks of embedding in global supply chains, responding to an increase in the need for personalized products and, most importantly, reducing costs and improving product quality. In addition to solving these problems, the enterprise has to deal with such problems as: overproduction, waiting and wasted time, defects and marriage. Despite the fact that economic efficiency is put at the forefront, in order to ensure the sustainable development of an enterprise, it is necessary the criteria of environmental friendliness, accident-free operation and social efficiency. Enterprises, whose competitive advantages are flexibility and response speed to market needs, require tools for the operational management of production and technological processes. For effective functioning within a complex system, planning and implementation of production and technological processes must be supported by appropriate information-analytical processes that provide the collection and analysis of information, as well as modeling and making control decisions for the production and technological process. Production management is carried out in the form of strategic, tactical and operational planning, which puts forward additional requirements for modeling tools and management decision support. A variety of neuro-fuzzy Petri nets with temporal fuzzy neurons is proposed. An example of building a model of the production process and the corresponding information-analytical processes is considered. The developed specialized software for modeling production and technological processes and the implementation of information- analytical processes, including modules for forming an ontological model of a complex system and processes, obtaining data, a neural network supervisor, building a model of a production- technological process and corresponding information-analytical processes using the mechanism constructors based on neuro-fuzzy temporal Petri nets is considered.
{"title":"Modeling and design of information-analytical production processes based on neuro-fuzzy temporal Petri nets","authors":"A. Bobryakov, V. Borisov, A. Misnik, S. Prakapenka","doi":"10.37791/2687-0649-2022-17-2-65-78","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-65-78","url":null,"abstract":"The article is devoted to the issues of modeling and designing information-analytical processes corresponding to the production and technological processes at the enterprise. In the modern conditions of the functioning of the market, the enterprise faces important tasks of embedding in global supply chains, responding to an increase in the need for personalized products and, most importantly, reducing costs and improving product quality. In addition to solving these problems, the enterprise has to deal with such problems as: overproduction, waiting and wasted time, defects and marriage. Despite the fact that economic efficiency is put at the forefront, in order to ensure the sustainable development of an enterprise, it is necessary the criteria of environmental friendliness, accident-free operation and social efficiency. Enterprises, whose competitive advantages are flexibility and response speed to market needs, require tools for the operational management of production and technological processes. For effective functioning within a complex system, planning and implementation of production and technological processes must be supported by appropriate information-analytical processes that provide the collection and analysis of information, as well as modeling and making control decisions for the production and technological process. Production management is carried out in the form of strategic, tactical and operational planning, which puts forward additional requirements for modeling tools and management decision support. A variety of neuro-fuzzy Petri nets with temporal fuzzy neurons is proposed. An example of building a model of the production process and the corresponding information-analytical processes is considered. The developed specialized software for modeling production and technological processes and the implementation of information- analytical processes, including modules for forming an ontological model of a complex system and processes, obtaining data, a neural network supervisor, building a model of a production- technological process and corresponding information-analytical processes using the mechanism constructors based on neuro-fuzzy temporal Petri nets is considered.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"17 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75426625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-93-104
E. Gumerov, T. V. Alekseeva
Oracle programs are a key link in the interaction of blockchain systems with the outside world. They must ensure the authenticity and security of data transmitted over a computer network to blockchain smart contracts. It is possible to increase security by creating a blockchain network for oracle programs, and a consensus of independent assessments of the authenticity of data in oracle programs will ensure the security of data transmitted to the main blockchain. Blockchain control systems in real time take several milliseconds to verify the authenticity of data, to data mining and to develop a control effect on the actuators. The consensus mechanism, which requires much more time, is not acceptable in these management systems. The purpose of this work is to develop the architecture of an intelligent information system of oracle programs for a real-time blockchain management system. To achieve the goal, the following tasks were solved: analysis of the state of the problem of ensuring the reliability and completeness of data, research of the capabilities of intelligent smart contracts, research of the intellectual capabilities of peripheral computing, development of the architecture of an intelligent information system of oracle programs. The scientific novelty of the work consists in the fact that a way has been found for high-speed transmission of the reliability of data transmitted by the oracle program system to the smart contracts of the blockchain management system in real time. The practical significance of the work is to solve the problem of providing reliable data to the blockchain management system in real time.
{"title":"Development of the architecture of an intelligent information system oracle programs blockchain management systems","authors":"E. Gumerov, T. V. Alekseeva","doi":"10.37791/2687-0649-2022-17-2-93-104","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-93-104","url":null,"abstract":"Oracle programs are a key link in the interaction of blockchain systems with the outside world. They must ensure the authenticity and security of data transmitted over a computer network to blockchain smart contracts. It is possible to increase security by creating a blockchain network for oracle programs, and a consensus of independent assessments of the authenticity of data in oracle programs will ensure the security of data transmitted to the main blockchain. Blockchain control systems in real time take several milliseconds to verify the authenticity of data, to data mining and to develop a control effect on the actuators. The consensus mechanism, which requires much more time, is not acceptable in these management systems. The purpose of this work is to develop the architecture of an intelligent information system of oracle programs for a real-time blockchain management system. To achieve the goal, the following tasks were solved: analysis of the state of the problem of ensuring the reliability and completeness of data, research of the capabilities of intelligent smart contracts, research of the intellectual capabilities of peripheral computing, development of the architecture of an intelligent information system of oracle programs. The scientific novelty of the work consists in the fact that a way has been found for high-speed transmission of the reliability of data transmitted by the oracle program system to the smart contracts of the blockchain management system in real time. The practical significance of the work is to solve the problem of providing reliable data to the blockchain management system in real time.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"37 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89712990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-45-64
V. Rozhkov, K. Krutikov, V. V. Fedotov, S. G. Butrimov
The article proposes a solution to the problem of accelerating the processes of self-starting of asynchronous electric motors of pumping equipment with the help of simulation computer modeling tools to reduce the negative impact on the power supply circuit of the auxiliary needs of a nuclear power plant. The features of the run-down transient processes and the interaction of machines of various capacities in the autonomous circuit that occurs after they are turned off, the subsequent transition to a backup power source, and the emerging effects during self-start are considered. It is shown that the most severe mode of such a transition occurs as a result of the operation of automatic switching on of the reserve and disconnection of working power sources by technological protections or actions of operational personnel at the operational level of operating voltage and nominal or close to it load sections. The analysis of emerging modes is carried out using models developed in the MatLab computer mathematics system with a built-in electrical application. The features of the processes of run-down and subsequent self-starting at various favorable and unfavorable moments of time and the magnitude of the mismatch between the voltages of the network and the resulting autonomous circuit are demonstrated. The models make it possible to obtain a reliable mathematical description of the electromagnetic and mechanical processes of motors in a complex electromechanical system of several motors, to measure the instantaneous voltage differences between the network and the run-down circuit, and to predict the optimal time to turn on the backup power source. The results of the studies carried out on the models are the development of recommendations on the technology for monitoring voltage and circuit mismatches for the same phases, the assessment of the root-mean-square deviation of these mismatches and the effective search for the moment of re-enabling the backup source to improve the technological modes of nuclear power plants.
{"title":"Modeling the process of self-starting of electric motors for auxiliary needs of a nuclear power plant to accelerate it and minimize various disturbances","authors":"V. Rozhkov, K. Krutikov, V. V. Fedotov, S. G. Butrimov","doi":"10.37791/2687-0649-2022-17-2-45-64","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-45-64","url":null,"abstract":"The article proposes a solution to the problem of accelerating the processes of self-starting of asynchronous electric motors of pumping equipment with the help of simulation computer modeling tools to reduce the negative impact on the power supply circuit of the auxiliary needs of a nuclear power plant. The features of the run-down transient processes and the interaction of machines of various capacities in the autonomous circuit that occurs after they are turned off, the subsequent transition to a backup power source, and the emerging effects during self-start are considered. It is shown that the most severe mode of such a transition occurs as a result of the operation of automatic switching on of the reserve and disconnection of working power sources by technological protections or actions of operational personnel at the operational level of operating voltage and nominal or close to it load sections. The analysis of emerging modes is carried out using models developed in the MatLab computer mathematics system with a built-in electrical application. The features of the processes of run-down and subsequent self-starting at various favorable and unfavorable moments of time and the magnitude of the mismatch between the voltages of the network and the resulting autonomous circuit are demonstrated. The models make it possible to obtain a reliable mathematical description of the electromagnetic and mechanical processes of motors in a complex electromechanical system of several motors, to measure the instantaneous voltage differences between the network and the run-down circuit, and to predict the optimal time to turn on the backup power source. The results of the studies carried out on the models are the development of recommendations on the technology for monitoring voltage and circuit mismatches for the same phases, the assessment of the root-mean-square deviation of these mismatches and the effective search for the moment of re-enabling the backup source to improve the technological modes of nuclear power plants.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"205 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88582406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-105-119
S. Kurilin, A. M. Sokolov, Nikolai N. Prokimnov
The article is aimed at solving the problem of scientific justification of criteria and methods for assessing the technical state of electromechanical systems based on the topological diagnostic method. Mathematical model and computer program for simulation of technical state indices of asynchronous electric motors (AEM) are presented. Functions and Green matrices, as well as deviation matrices, are considered as such indicators. The basis of the program is the mathematical model of the AEM with a non-accelerated rotor and non-homogeneous windings. AEM is supplied from pulse voltage source. The action is carried out in different directions of the vector space of the motor in order to determine its characteristics and degree of homogeneity. Based on the reactions of the object, the program calculates and analyzes technical indicators for intact and damaged states of the AEM. A computer program for mathematical modeling of the technical state indicators of the AEM was carried out using the Maple package of symbolic and numerical calculations, which provides extensive opportunities for mathematical studies of various levels. A description of a software implementation of the proposed mathematical model is given. An example of using a program to model the performance of a serial motor with specified technical characteristics is given. The article presents the results of modeling the object indicators corresponding to the object different operational states. A reference state, a damaged state characterized by a change in the properties of the vector space during long-term operation, as well as a limit state, which corresponds to a break in one of the phases of the rotor winding, were defined as these states. Conclusions on each of the given electric motor states are given.
{"title":"Computer program for modeling of technical state indicators of electromechanical systems","authors":"S. Kurilin, A. M. Sokolov, Nikolai N. Prokimnov","doi":"10.37791/2687-0649-2022-17-2-105-119","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-105-119","url":null,"abstract":"The article is aimed at solving the problem of scientific justification of criteria and methods for assessing the technical state of electromechanical systems based on the topological diagnostic method. Mathematical model and computer program for simulation of technical state indices of asynchronous electric motors (AEM) are presented. Functions and Green matrices, as well as deviation matrices, are considered as such indicators. The basis of the program is the mathematical model of the AEM with a non-accelerated rotor and non-homogeneous windings. AEM is supplied from pulse voltage source. The action is carried out in different directions of the vector space of the motor in order to determine its characteristics and degree of homogeneity. Based on the reactions of the object, the program calculates and analyzes technical indicators for intact and damaged states of the AEM. A computer program for mathematical modeling of the technical state indicators of the AEM was carried out using the Maple package of symbolic and numerical calculations, which provides extensive opportunities for mathematical studies of various levels. A description of a software implementation of the proposed mathematical model is given. An example of using a program to model the performance of a serial motor with specified technical characteristics is given. The article presents the results of modeling the object indicators corresponding to the object different operational states. A reference state, a damaged state characterized by a change in the properties of the vector space during long-term operation, as well as a limit state, which corresponds to a break in one of the phases of the rotor winding, were defined as these states. Conclusions on each of the given electric motor states are given.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"16 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90389603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-120-132
A. Misnik
The article deals with the issues of ontological engineering of complex systems. Ontological engineering includes the processes of designing and building ontologies, technologically combining object-oriented and structural analysis. Ontological engineering aims to ensure the adoption of high-quality management decisions by increasing the level of integration of the necessary information, improving search capabilities in databases and knowledge bases, providing the possibility of joint processing of knowledge based on a single semantic description of the knowledge space. This process is carried out within the framework of the proposed approach to managing complex systems. The ontology obtained as a result of engineering is subject to the requirements of convenience and flexibility, which is necessary for modeling system processes and ensuring the functioning of information and analytical processes in a complex system. The application of ordinary graphs, hypergraphs and metagraphs in ontological engineering is described. The use of metagraphs in the construction of hierarchical ontologies is substantiated. Metagraphs are considered as the basis for building an applied ontology of a complex system. A modification of the metagraph is proposed, which makes it possible to include events and data processing methods in the ontology. Such a modification integrates the process component into the ontological model of the system as an integral part of it, which makes it possible to flexibly and with less time to form process models based on the metagraph subgraphs of the general ontological model. An approach and an example of the implementation of the software-instrumental environment of ontological engineering and further construction of models of processes of a complex system are described. The technology used to implement the ontology in the PostgreSQL database management system and the database structure for storing the ontology are described
{"title":"Metagraphs for ontological engineering of complex systems","authors":"A. Misnik","doi":"10.37791/2687-0649-2022-17-2-120-132","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-120-132","url":null,"abstract":"The article deals with the issues of ontological engineering of complex systems. Ontological engineering includes the processes of designing and building ontologies, technologically combining object-oriented and structural analysis. Ontological engineering aims to ensure the adoption of high-quality management decisions by increasing the level of integration of the necessary information, improving search capabilities in databases and knowledge bases, providing the possibility of joint processing of knowledge based on a single semantic description of the knowledge space. This process is carried out within the framework of the proposed approach to managing complex systems. The ontology obtained as a result of engineering is subject to the requirements of convenience and flexibility, which is necessary for modeling system processes and ensuring the functioning of information and analytical processes in a complex system. The application of ordinary graphs, hypergraphs and metagraphs in ontological engineering is described. The use of metagraphs in the construction of hierarchical ontologies is substantiated. Metagraphs are considered as the basis for building an applied ontology of a complex system. A modification of the metagraph is proposed, which makes it possible to include events and data processing methods in the ontology. Such a modification integrates the process component into the ontological model of the system as an integral part of it, which makes it possible to flexibly and with less time to form process models based on the metagraph subgraphs of the general ontological model. An approach and an example of the implementation of the software-instrumental environment of ontological engineering and further construction of models of processes of a complex system are described. The technology used to implement the ontology in the PostgreSQL database management system and the database structure for storing the ontology are described","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"13 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78936284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-79-92
E. Kirillova, A. Lazarev, Oleg P. Kultygin
Currently, the specifics of external conditions and peculiarities of innovation activity main subjects development determine not only the need for close, long-term scientific and technical cooperation with the state for the sustainable development of territories, but also the need to develop and substantiate proposals for managing the development of innovation processes in such a system as a whole. The article proposes a model for the representation of scientific and industrial interaction in the implementation of regional innovation processes in the form of a three-dimensional "slice" of the triple helix as a resource VRIO-profile of cooperative formation, which allows to clearly demonstrate the system of relations, identify in which direction the problem area is, influencing which it will be possible to return the system to an equilibrium state of sustainable development in a strategic perspective. The analysis of modern scientific works shows the relevance, necessity and effectiveness of using methods based on neural networks to predict changes in the state of complex socio-economic systems, such as regional innovation systems. Existing approaches, as a rule, demonstrate a narrow focus and belonging to a separate enterprise or organization, and therefore do not meet all the requirements from both the implementation of the innovation process itself and the modification of the external environment. In this connection, the authors proposed an information and analytical solution for using the described model to support decision-making on the management of cooperative formations. The developed program is based on predicting the future state (position in a three-dimensional coordinate system) of the system using deep neural networks, namely recurrent. The described practical approbation of the model can in the future serve as a basis for decision-making on the choice of forms and directions of interaction of cooperative formations in the strategic perspective.
{"title":"Neural network model to support decision-making on managing cooperative relations in innovative ecosystems","authors":"E. Kirillova, A. Lazarev, Oleg P. Kultygin","doi":"10.37791/2687-0649-2022-17-2-79-92","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-79-92","url":null,"abstract":"Currently, the specifics of external conditions and peculiarities of innovation activity main subjects development determine not only the need for close, long-term scientific and technical cooperation with the state for the sustainable development of territories, but also the need to develop and substantiate proposals for managing the development of innovation processes in such a system as a whole. The article proposes a model for the representation of scientific and industrial interaction in the implementation of regional innovation processes in the form of a three-dimensional \"slice\" of the triple helix as a resource VRIO-profile of cooperative formation, which allows to clearly demonstrate the system of relations, identify in which direction the problem area is, influencing which it will be possible to return the system to an equilibrium state of sustainable development in a strategic perspective. The analysis of modern scientific works shows the relevance, necessity and effectiveness of using methods based on neural networks to predict changes in the state of complex socio-economic systems, such as regional innovation systems. Existing approaches, as a rule, demonstrate a narrow focus and belonging to a separate enterprise or organization, and therefore do not meet all the requirements from both the implementation of the innovation process itself and the modification of the external environment. In this connection, the authors proposed an information and analytical solution for using the described model to support decision-making on the management of cooperative formations. The developed program is based on predicting the future state (position in a three-dimensional coordinate system) of the system using deep neural networks, namely recurrent. The described practical approbation of the model can in the future serve as a basis for decision-making on the choice of forms and directions of interaction of cooperative formations in the strategic perspective.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"50 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84704451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.37791/2687-0649-2022-17-2-31-44
Tatyana V. Gaibova, P. Sakhnyuk
The article deals with the problem of organizing training for data scientists and data analytics specialists using information technologies. The authors analyzed the current sets of competencies of data science and analytics, identified the problems of organizing their development, considered modern trends in the instrumental support of the learning process. Particular attention is paid to the peculiarities of the development of soft skills in data science and analytics, which should be taken into account in systems and platforms for learning support when building models for the formation of personalized content and learning paths within the course. The necessity of creating a multi-agent software application to support the pedagogical design of the course is substantiated, which allows to adapt the capabilities of modern software systems and learning platforms to increase the efficiency of group interaction and the formation of soft skills necessary in the implementation of data analysis projects. The results of the conceptual design of a multi-agent application integrated with modern learning platforms are presented: a UML diagram of use cases is proposed that provides support for the personalization of training not only at the individual, but also at the command level, the base classes of agents are highlighted and an ontological model is developed to support the formation of soft skills in data science and analytics, directions of further research are determined. The results obtained will be useful to support the formation of a full set of competencies for data science and analytics, as well as to increase the efficiency of group work and support the personalization of content in a hybrid or online learning format, both in the higher education system and in corporate divisions.
{"title":"Instrumental support of technologies for organizing group training for the development of soft skills in data science and analytics","authors":"Tatyana V. Gaibova, P. Sakhnyuk","doi":"10.37791/2687-0649-2022-17-2-31-44","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-2-31-44","url":null,"abstract":"The article deals with the problem of organizing training for data scientists and data analytics specialists using information technologies. The authors analyzed the current sets of competencies of data science and analytics, identified the problems of organizing their development, considered modern trends in the instrumental support of the learning process. Particular attention is paid to the peculiarities of the development of soft skills in data science and analytics, which should be taken into account in systems and platforms for learning support when building models for the formation of personalized content and learning paths within the course. The necessity of creating a multi-agent software application to support the pedagogical design of the course is substantiated, which allows to adapt the capabilities of modern software systems and learning platforms to increase the efficiency of group interaction and the formation of soft skills necessary in the implementation of data analysis projects. The results of the conceptual design of a multi-agent application integrated with modern learning platforms are presented: a UML diagram of use cases is proposed that provides support for the personalization of training not only at the individual, but also at the command level, the base classes of agents are highlighted and an ontological model is developed to support the formation of soft skills in data science and analytics, directions of further research are determined. The results obtained will be useful to support the formation of a full set of competencies for data science and analytics, as well as to increase the efficiency of group work and support the personalization of content in a hybrid or online learning format, both in the higher education system and in corporate divisions.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"31 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87169899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-31DOI: 10.37791/2687-0649-2022-17-1-39-54
Dmetry A. Tukmakovkov
This work is devoted to mathematical modeling of the dynamics of inhomogeneous electrically charged media. A dusty environment - solid particles suspended in a gas – was considered as an inhomogeneous medium. The mathematical model implemented a continuous approach to modeling the dynamics of inhomogeneous media. The complete hydrodynamic system of equations was solved for each component. The system of equations for the dynamics of each component included the equations of mass continuity, momentum components, and the energy conservation equation for the mixture component. Intercomponent interaction took into account momentum exchange and intercomponent heat transfer. The carrier medium was described as a viscous compressible heat-conducting gas. The flow was described as a flow with a two- dimensional geometry. The equations of the mathematical model were supplemented with initial and boundary conditions. The mathematical model took into account the wall viscosity in the channel. The system of equations of the mathematical model was integrated by McCormack's explicit finite-difference method. To obtain a monotonic grid function, a nonlinear scheme for correcting the numerical solution was used. The mathematical model was supplemented by the Poisson equation describing the electric field formed by charged dispersed particles. Poisson's equation was integrated by finite-difference methods on a gas-dynamic grid. Such a choice of the computational grid was necessary to calculate the concentration of particles required both for solving the electric field equation and for calculating the physical fields of the dynamics of inhomogeneous media. The reciprocal motion of a gas suspension caused by the movement of dispersed particles under the action of the Coulomb force was numerically investigated. The values of the surface and mass densities are determined, at which the models of the surface and mass densities of charges in the simulation of such a process are the same. It is revealed that the surface and mass models of charges are identical with respect to the volumetric content.
{"title":"Comparison of mathematical models of the dynamics of electrically charged gas suspensions for various concentrations of the dispersed component","authors":"Dmetry A. Tukmakovkov","doi":"10.37791/2687-0649-2022-17-1-39-54","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-39-54","url":null,"abstract":"This work is devoted to mathematical modeling of the dynamics of inhomogeneous electrically charged media. A dusty environment - solid particles suspended in a gas – was considered as an inhomogeneous medium. The mathematical model implemented a continuous approach to modeling the dynamics of inhomogeneous media. The complete hydrodynamic system of equations was solved for each component. The system of equations for the dynamics of each component included the equations of mass continuity, momentum components, and the energy conservation equation for the mixture component. Intercomponent interaction took into account momentum exchange and intercomponent heat transfer. The carrier medium was described as a viscous compressible heat-conducting gas. The flow was described as a flow with a two- dimensional geometry. The equations of the mathematical model were supplemented with initial and boundary conditions. The mathematical model took into account the wall viscosity in the channel. The system of equations of the mathematical model was integrated by McCormack's explicit finite-difference method. To obtain a monotonic grid function, a nonlinear scheme for correcting the numerical solution was used. The mathematical model was supplemented by the Poisson equation describing the electric field formed by charged dispersed particles. Poisson's equation was integrated by finite-difference methods on a gas-dynamic grid. Such a choice of the computational grid was necessary to calculate the concentration of particles required both for solving the electric field equation and for calculating the physical fields of the dynamics of inhomogeneous media. The reciprocal motion of a gas suspension caused by the movement of dispersed particles under the action of the Coulomb force was numerically investigated. The values of the surface and mass densities are determined, at which the models of the surface and mass densities of charges in the simulation of such a process are the same. It is revealed that the surface and mass models of charges are identical with respect to the volumetric content.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"110 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76081273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-30DOI: 10.37791/2687-0649-2022-17-1-5-18
A. E. Zubanova, A. Morozov, A. E. Trubin, A. N. Aleksahin, S. Novikov
The article justifies actuality of application of neural network methods for identification of significant predictors of the transport and logistics infrastructure of regions of the Russian Federation. The condition of the logistics industry of the Russian Federation in comparison with foreign countries has been analyzed. It was concluded that it is necessary to increase the accuracy of estimation of indicators of transport and logistics infrastructure of regions in order to identify their impact on the development of logistics. The problem of the traditional methodology of building a model of transport and logistics infrastructure of regions based on the application of mathematical and econometric analysis lies in the inability of the latter to find and accurately describe the non-obvious dependencies in the data. The expediency of sequential coupling of econometric and neural network research tools has been determined. The two-step procedure of identification of factors influencing the logistics development of the Russian Federation has been tested. As a result, it was possible to select the most significant socio-economic (average per capita income of the population, retail trade turnover, imports of the subjects of the Russian Federation) and infrastructure factors (the share of paved roads, the shipment of goods by public rail, the departure of passengers by public rail, the density of public railway) logistics infrastructure on the basis of an econometric approach. In the second step of the study, a neural network model of the remaining factors was developed based on the development of classification trees and a neural network, acting as a kind of computational filter, which allowed solving the problem of attribution of macroeconomic data and achieving a high level of significance of forecasts. The proposed approach of sequential coupling of econometric methods and neural network modelling has universality and practical importance, therefore it is applicable to the study of a wide range of macroeconomic processes.
{"title":"Synergy of econometric approach and use of neural networks to determine factors of provision of transport and logistics infrastructure in regions of Russia","authors":"A. E. Zubanova, A. Morozov, A. E. Trubin, A. N. Aleksahin, S. Novikov","doi":"10.37791/2687-0649-2022-17-1-5-18","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-5-18","url":null,"abstract":"The article justifies actuality of application of neural network methods for identification of significant predictors of the transport and logistics infrastructure of regions of the Russian Federation. The condition of the logistics industry of the Russian Federation in comparison with foreign countries has been analyzed. It was concluded that it is necessary to increase the accuracy of estimation of indicators of transport and logistics infrastructure of regions in order to identify their impact on the development of logistics. The problem of the traditional methodology of building a model of transport and logistics infrastructure of regions based on the application of mathematical and econometric analysis lies in the inability of the latter to find and accurately describe the non-obvious dependencies in the data. The expediency of sequential coupling of econometric and neural network research tools has been determined. The two-step procedure of identification of factors influencing the logistics development of the Russian Federation has been tested. As a result, it was possible to select the most significant socio-economic (average per capita income of the population, retail trade turnover, imports of the subjects of the Russian Federation) and infrastructure factors (the share of paved roads, the shipment of goods by public rail, the departure of passengers by public rail, the density of public railway) logistics infrastructure on the basis of an econometric approach. In the second step of the study, a neural network model of the remaining factors was developed based on the development of classification trees and a neural network, acting as a kind of computational filter, which allowed solving the problem of attribution of macroeconomic data and achieving a high level of significance of forecasts. The proposed approach of sequential coupling of econometric methods and neural network modelling has universality and practical importance, therefore it is applicable to the study of a wide range of macroeconomic processes.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"88 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84364723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-30DOI: 10.37791/2687-0649-2022-17-1-27-38
V. Borisov, S. Kurilin, V. Luferov
The effectiveness of fuzzy cognitive modeling methods for analyzing and predicting the state of complex technical systems (STS) is justified by the following reasons: significant interdependence, non-linear nature and incompleteness of information about the mutual influence of the analyzed parameters of the CTS; a variety of effects of internal and external factors on the CTS; complexity and cost of conducting experimental studies during the operation of these systems. The main limitations of fuzzy cognitive models for modeling STS dynamics are: the complexity of taking into account the mutual influence of parameters with their different time lags relative to each other; the need for their constant operational adjustment and training of component models for all parameters during the operation of the CTS. In this paper, Fuzzy Relational Cognitive Temporal Models (FRCTM) are developed. These models combine the advantages of various types of fuzzy cognitive models, and at the same time neutralize the main limitations of the analysis and prediction of the state of the CTS, which are inherent in the well- known fuzzy cognitive models. The paper also proposes models of system dynamics that take into account the specifics of the FRCTM. We have also developed an approach and implemented a method for calculating fuzzy dependencies in vector-matrix form for dynamic modeling of the CTS. The proposed method makes it possible to solve the problems of increasing the uncertainty of the results and the output of fuzzy values of the FRCTM concepts beyond the ranges of the base sets due to the execution of mass iterative computations. An example of modeling heterogeneous electromechanical systems based on FRCTM is given. The results obtained are the basis for solving a whole range of tasks of analysis, predictive evaluation, modeling of different scenarios of the functioning and development of heterogeneous electromechanical systems for various system factors, operating modes and external conditions.
{"title":"Fuzzy relational cognitive temporal models for analyzing and state prediction of complex technical systems","authors":"V. Borisov, S. Kurilin, V. Luferov","doi":"10.37791/2687-0649-2022-17-1-27-38","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-27-38","url":null,"abstract":"The effectiveness of fuzzy cognitive modeling methods for analyzing and predicting the state of complex technical systems (STS) is justified by the following reasons: significant interdependence, non-linear nature and incompleteness of information about the mutual influence of the analyzed parameters of the CTS; a variety of effects of internal and external factors on the CTS; complexity and cost of conducting experimental studies during the operation of these systems. The main limitations of fuzzy cognitive models for modeling STS dynamics are: the complexity of taking into account the mutual influence of parameters with their different time lags relative to each other; the need for their constant operational adjustment and training of component models for all parameters during the operation of the CTS. In this paper, Fuzzy Relational Cognitive Temporal Models (FRCTM) are developed. These models combine the advantages of various types of fuzzy cognitive models, and at the same time neutralize the main limitations of the analysis and prediction of the state of the CTS, which are inherent in the well- known fuzzy cognitive models. The paper also proposes models of system dynamics that take into account the specifics of the FRCTM. We have also developed an approach and implemented a method for calculating fuzzy dependencies in vector-matrix form for dynamic modeling of the CTS. The proposed method makes it possible to solve the problems of increasing the uncertainty of the results and the output of fuzzy values of the FRCTM concepts beyond the ranges of the base sets due to the execution of mass iterative computations. An example of modeling heterogeneous electromechanical systems based on FRCTM is given. The results obtained are the basis for solving a whole range of tasks of analysis, predictive evaluation, modeling of different scenarios of the functioning and development of heterogeneous electromechanical systems for various system factors, operating modes and external conditions.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"186 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89561480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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