№ 153(9), November, 2019
Public date: 29.11.2019
Archive of journal: Articles count 26, 77 kb
-
05.13.18 Mathematical modeling, numerical methods and software complexes
05.13.18 Mathematical modeling, numerical methods and software complexes
DescriptionIn the process of formation of nonlinear dynamics, the scientific society was able to refute the classical mechanisms of Newton-Laplace by justifying the chaotic nature of the phenomena of the world. However, despite the emergence of new mathematical models and tools, forecasting of nonlinear systems is a difficult task, as not only the quantitative and qualitative characteristics of the factors affecting the system are unknown, but also there is a problem of a small amount of information for forecasting. In this article, the authors consider the linear cellular apparatus as a tool for prediction the final state, to which the system will come based only on its output indicators of previous years. Since the use of a linear cellular automaton for prediction of nonlinear systems is an assumption of the authors, it should be tested on the series of stochastic systems exposed to different risk factors, which together give either a positive response of the system or a negative one. An example of such series is the time series of yields, as it is affected by climatic conditions, the appearance of which, in turn, is also difficult to predict. Prediction of stochastic systems using linear cellular automaton really makes it possible to get adequate and visual models. Due to the fact that the forecast model has a discrepancy with the real result of 0-15% (both positive and negative), the conclusion is that the predicted value will help either to take measures to ensure that the real value in the future is not lower, or to make sure that the decisions and measures taken are correct, when a value is higher than the forecast
-
05.13.10 Management in social and economic systems
MULTI-CRITERIA ANALYSIS OF ALTERNATIVES IN SOLVING HUMAN RESOURCES MANAGEMENT PROBLEMS
05.13.10 Management in social and economic systems
DescriptionHuman resources have recently reasonably gained more and more importance. Today, along with material, intellectual, informational and financial resources, they affect the efficiency of enterprises and organizations. Competent assessment of human resources, a clear understanding of means of interaction with staff and developing human potential are the basis for the effective work of both human resources departments and organizations as a whole. The complexity of assessing human resources necessitates the development of a toolkit, the use of which will simplify it and ensure that one receives the most accurate advice and assistance in making management decisions. A promising direction for the implementation of the designated toolkit may be the development of a decision support system, within which, among other things, the possibility of a multi-criteria analysis of alternatives will be available. Due to the fact that there are no methods for multi-criteria analysis of alternatives intended solely for assessing human resources, it is necessary to conduct a thorough analysis, the main purpose of which is to identify the most suitable basis for further adaptation and development. After conducting preliminary studies, the TOPSIS, MAUT, AHP and ELECTRE methods were chosen as the most promising for solving the problem
-
05.13.10 Management in social and economic systems
DescriptionThe article discusses modern approaches to the implementation of the migration of virtual machines between different virtualization platforms. A comparative characteristic of virtual migration tools is given. Conclusions are drawn on the expediency of applying different approaches depending on the task facing migration and available resources. The author presents a technique for migrating virtual machines from VMware vSphere virtualization platform to Microsoft Hyper-V virtualization platform, which allows to increase the speed and reliability of the migration process and significantly save on operating costs of the company
-
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
-
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)
-
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