Conceptual approaches to the interaction of labor market entities and educational institutions in the Russian Federation within the ecosystem based on neural network mechanisms

Elena Eduardovna Alenina; Vera Vitalievna Ziulina; Ilya Aleksandrovich Alenin; Sergey Vladimirovich Bolotnikov; Dmitry Vladimirovich Redin; Lyubov Viktorovna Borodacheva

doi:10.22633/rpge.v25iesp.5.16016

Autores

Elena Eduardovna Alenina Moscow Polytechnic University, Moscow – Russia https://orcid.org/0000-0002-0109-3064
Vera Vitalievna Ziulina Moscow Polytechnic University, Moscow – Russia https://orcid.org/0000-0002-9419-1121
Ilya Aleksandrovich Alenin Moscow Polytechnic University, Moscow – Russia https://orcid.org/0000-0002-7373-2419
Sergey Vladimirovich Bolotnikov Moscow Polytechnic University, Moscow – Russia https://orcid.org/0000-0002-3419-2800
Dmitry Vladimirovich Redin Moscow Polytechnic University, Moscow – Russia https://orcid.org/0000-0003-4165-6885
Lyubov Viktorovna Borodacheva Moscow Polytechnic University, Moscow – Russia https://orcid.org/0000-0001-7778-2854

DOI:

https://doi.org/10.22633/rpge.v25iesp.5.16016

Palavras-chave:

Sistemas de redes neurais, Descrição, Modelagem, BPMN 2.0, Mineração de dados, Comunicação dirigida, Interação orientada a documentos, Soluções de gerenciamento, Instituições educacionais

Resumo

O objetivo do estudo: desenvolver e descrever, o processo de funcionamento de um sistema de rede neural de justificação pericial de decisões de gestão no domínio da preparação de programas educacionais para atividades promissoras utilizando métodos de modelagem gráfica. Resultados: foram propostas abordagens conceituais para garantir a interação de entidades do mercado de trabalho e organizações educacionais da Federação Russa dentro do ecossistema de informação e comunicação com base em mecanismos de rede neural descritos na notação BPMN 2.0. Os principais temas do sistema foram caracterizados através das ferramentas "pool" e "swimline", a sua interação através das ferramentas "flow", "fluxos de mensagens", as principais operações apresentadas através de processos privados de mineração de dados, IDSS, comunicação dirigida e interação documental dirigida. A novidade científica do estudo: foi proposto o conceito de interação estratégica entre os sujeitos do mercado de trabalho e as instituições de ensino da Federação Russa com base na automação da comunicação e no uso de mecanismos de rede neural.

Downloads

Não há dados estatísticos.

Biografia do Autor

Elena Eduardovna Alenina, Moscow Polytechnic University, Moscow – Russia

Assistant Professor.

Vera Vitalievna Ziulina, Moscow Polytechnic University, Moscow – Russia

Assistant Professor.

Ilya Aleksandrovich Alenin, Moscow Polytechnic University, Moscow – Russia

Lecturer.

Sergey Vladimirovich Bolotnikov, Moscow Polytechnic University, Moscow – Russia

Assistant Professor.

Dmitry Vladimirovich Redin, Moscow Polytechnic University, Moscow – Russia

Professor.

Lyubov Viktorovna Borodacheva, Moscow Polytechnic University, Moscow – Russia

Senior Lecturer.

Referências

ALENINA, E. E. et al. Management tools in modern distributed social communities. Laplage em Revista, 7(Extra-C), p. 48-56, 2021. DOI: 10.24115/S2446-622020217Extra-C983p.48-56

BOLOTNIKOV, S. V.; VASIN, V. A. Specialist as an element of the artificial intelligence system [Specialst kak element sistemy iskusstvennogo intellekta]. Science and business: ways of development, v. 9, n. 99, p. 79-83, 2019.

BOLOTNIKOV, S. V.; VASIN, V. A.; SENDEROV, V. L. Neural network interaction of expert councils in the interests of strategic decision-making [Nejrosetevoe vzaimodejstvie ekspertnyh sovetov v interesah prinyatiya strategicheskih reshenij]. "Global scientific potential", v. 12, n. 81, p. 43-47, 2017

GAO, Z. M. et al. Application of Deep Q-Network in Portfolio Management. In: IEEE INTERNATIONAL CONFERENCE ON BIG DATA ANALYTICS, 5., 2020. Proceedings […]. 2020. p. 268-275.

LI, X. T.; SUN, Y. Application of RBF neural network optimal segmentation algorithm in credit rating. Neural Computing, and Applications, v. 14, p. 8227-8235, 2021. DOI: 10.1007/s00521-020-04958-9

MAZUR, V. V.; SENDEROV, V. L. The mechanism of neural network change management in the process of vocational education [Mekhanizm nejrosetevogo upravleniya izmeneniyami v processe professionalnogo obrazovaniya]. In: INTERNATIONAL SCIENTIFIC-PRACTICAL CONFERENCE OF THE DEPARTMENT OF MANAGEMENT, MODERN PROBLEMS OF MANAGING THE COMPETITIVENESS AND INNOVATIVE DEVELOPMENT OF RUSSIA ON THE BASIS OF DIGITAL TECHNOLOGIES, 7., 2019, Moscow. Proceedings […]. Moscow: Moscow Polytech, 2019. p. 55-59.

MOSKALENKO, V.; FONTA, N. The Method of Constructing a Development Trajectory as the Basis of an Intelligent Module for Strategic Planning of the EPM System. In: INTERNATIONAL CONFERENCE ON COMPUTATIONAL LINGUISTICS AND INTELLIGENT SYSTEMS, 5., 2021. Proceedings […]. Main Conference, Colins 2021. v. 1.

PETROVA, A. K. Application of Neural Networks in the HR Tasks. In: IEEE CONFERENCE OF RUSSIAN YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING (ELCONRUS), 2021, Saint Petersburg. Proceedings […]. Saint Petersburg, Russia: Saint Petersburg Electrotechn Univ, 2021. p. 582-585. DOI: 10.1109/ElConRus51938.2021.9396480

WU, Y. C.; FENG, J. W. Development and Application of Artificial Neural Network. Wireless Personal Communications, v. 102, n. 2, p. 1645-1656, 2018. DOI: 10.1007/s11277-017-5224-x

ZHENG, J. F.; MA, R. J. Analysis of Enterprise Human Resources Demand Forecast Model Based on SOM Neural Network. Computational Intelligence, and Neuroscience, v. 5, p. 1-10, 2021. DOI: 10.1155/2021/6596548