05.13.10 Management in social and economic systems
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NEURO-FUZZY CONTROL MODEL OF AN INNOVATION-ACTIVE COMPANY MANAGEMENT
05.13.10 Management in social and economic systems
DescriptionThe article discusses the concept and the principles of the organization of neuro-fuzzy management of an innovation-active enterprise based on intelligent technologies and high-performance computing tools. The developed information model provides operational control of the current situations caused by innovations in the complex dynamic conditions of the changing market conditions. Particular attention is paid to solving the problem of planning operations and developing management decisions when implementing the principle of competition in the face of uncertainty and incompleteness of the initial information. The developed software implementation of the fuzzy ranking of management solutions options is publicly available on ws-dss.com
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MODELING AND DIAGNOSTICS OF THE RESEARCHER’S SYNERGIC INTERACTION WITH THE SCIENTIFIC COMMUNITY
05.13.10 Management in social and economic systems
DescriptionThe article presents innovative models and methods to diagnose the researcher’s synergic interaction with the scientific community (social mega-environment). It is known that the researcher’s interaction with the social mega-environment has two main directions: scientific collaboration and using the scientific community’s social and cultural potential; the former appears as scientific publications, while the latter appears as scientific citations. It is also known that synergic interaction is the interaction leading to the increase in activity results (according to the “1+1>2” scheme). In the article, the researcher’s synergic interaction is understood as his/her collaboration-based research activity that leads to obtaining the results impossible without this interaction. The theoretical significance of the research results is in the possibility for the further development of the sociology of science, as well as for the further development of the models of the individual’s interaction with the social environment; the practical significance is in the possibility to analyze the factors contributing to the success in the research activity of academic researchers and research teams (i.e. applicable for monitoring the research activity)
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USING NEURAL NETWORKS FOR THE PROJECT TEAM SELECTION
05.13.10 Management in social and economic systems
DescriptionThe study was carried out with the financial support of the RHNF as part of the research project of the RFBR 17-02-00475-OGN "Application of metaheuristic algorithms for solving direct and inverse problems of optimizing the management of spatially distributed complexes"). The article considers the issue of automated selection of specialists for the project. It is proposed to use artificial neural networks as a decisive core of the system. We have considered several solutions to the problem with a basic version based on a cascade of two neural networks