Подходы к прогнозированию изменения состояния обеспечивающих компонентов информационно-управляющей системы
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Approaches to predicting changes in the state of supporting components of an information management system

idShevnina Y.S. idRyabov P.E. idProkopchina S.V. idKochkarov R.A.

UDC 004.9
DOI: -

  • Abstract
  • List of references
  • About authors

The article presents approaches to predicting the dynamics of the state of supporting components of information and control systems using the example of modeling the power system of a manufacturing enterprise. A method for modeling other types of supporting components based on the proposed approaches is considered. Modeling the state of the power system of a manufacturing enterprise is based on its representation in the form of a set of T-shaped cells consisting of resistance, capacitance and inductance. Forecasting changes in the state of the supporting components of the information and control system is carried out using a multilayer feed-forward neural network, taking into account nonlinear factors determined by the external and internal state of the production environment. Environmental parameters, data on depreciation of actuators and equipment, and regulatory production requirements are used as independent variables, and the power of the enterprise's energy system is used as a dependent variable. In this case, the power calculation is carried out on the basis of the described power system model using T-shaped cells. The model was trained on the basis of accumulated data. The obtained results of modeling the state of the supporting components of information control systems show that using a feedforward neural network model with one hidden layer and six nodes in it to predict the dynamics allows one to obtain an accurate power forecast taking into account various nonlinear factors. Experimental data are presented that prove the effectiveness of the approaches proposed by the authors for predicting the state of supporting components.

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Shevnina Yulia Sergeevna
Candidate of Technical Sciences, Associate Professor

ORCID |

National Research University MIET

Moscow, Russia

Ryabov Pavel Evgen’evich
Doctor of Physical and Mathematical Sciences, Associate Professor

ORCID |

Financial University under the Government of the Russian Federation

Moscow, Russia

Prokopchina Svetlana Vasil’evna
Doctor of Technical Sciences, Professor

ORCID |

Financial University under the Government of the Russian Federation

Moscow, Russia

Kochkarov Rasul Ahmatovich
Candidate of Economic Sciences, Associate Professor

ORCID |

Financial University under the Government of the Russian Federation

Moscow, Russia

Keywords: information and control systems, state forecasting, nonlinear factors, power systems, feedforward neural network

For citation: Shevnina Y.S. Ryabov P.E. Prokopchina S.V. Kochkarov R.A. Approaches to predicting changes in the state of supporting components of an information management system. Modeling, Optimization and Information Technology. 2024;12(2). Available from: https://moitvivt.ru/ru/journal/pdf?id=1549 DOI: - (In Russ).

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Full text in PDF

Received 03.04.2024

Revised 13.05.2024

Accepted 15.05.2024