Forming entropy-information assessment correspondence of complex objects state and knowledge-oriented databases in monitoring systems

Authors

  • Tatiana V. Kozulia The Department of Software Engineering and Management Information Technologies of National Technical University "Kharkiv Polytechnic Institute", Kharkiv, Ukraine https://orcid.org/0000-0001-5107-9140
  • V. F. Moiseev The Department of chemical engineering and industrial ecology of National Technical University "Kharkiv Polytechnic Institute", Kharkiv, Ukraine https://orcid.org/0000-0002-3217-1467
  • Mariia M. Kozulia The Department of Software Engineering and Management Information Technologies of National Technical University "Kharkiv Polytechnic Institute", Kharkiv, Ukraine https://orcid.org/0000-0002-4090-8481
  • Anatolii V. Savchenko The Department of internal combustion engines of National Technical University "Kharkiv Polytechnic Institute", Kharkiv, Ukraine https://orcid.org/0000-0002-4732-2045

DOI:

https://doi.org/10.20535/SRIT.2308-8893.2018.2.10

Keywords:

complex systems, інформаційно-методичне забезпечення, entropy-information model, monitoring information, entropy state function, knowledge-oriented system

Abstract

The knowledge-based approach for complex systems assessment and forecasting is justified. Production systems of the form "object 0-state (as the system components) – process (system processes, status change operator or support) – object i-state (system)" are discussed along with the problems of the information support development for implementing the methodological foundation for the complex monitoring systems analysis. The basis for the information-entropy approach is determined for forming models for objects of study with the purpose of object analysis of the state of natural and technogenic origin systemic formations using knowledge-oriented data and generating new knowledge. The information system is shown for collecting and storing the status data of the object of study under monitoring, transmitting data to generate models, analyzing the results and making an informed decision.

Author Biographies

Tatiana V. Kozulia, The Department of Software Engineering and Management Information Technologies of National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Tatiana Kozulia,

Doctor of technical sciences, a professor at the Department of Software Engineering and Management Information Technologies of National Technical University "Kharkiv Polytechnic Institute", Kharkiv, Ukraine.

V. F. Moiseev, The Department of chemical engineering and industrial ecology of National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Victor Moiseev,

Candidate of technical science (Ph.D.), a professor at the Department of chemical engineering and industrial ecology of National Technical University "Kharkiv Polytechnic Institute", Kharkiv, Ukraine.

Mariia M. Kozulia, The Department of Software Engineering and Management Information Technologies of National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Mariia Kozulia,

Candidate of technical science (Ph.D.), an associate professor at the Department of Software Engineering and Management Information Technologies of National Technical University "Kharkiv Polytechnic Institute", Kharkiv, Ukraine.

Anatolii V. Savchenko, The Department of internal combustion engines of National Technical University "Kharkiv Polytechnic Institute", Kharkiv

Anatolii Savchenko,

a junior researcher at the Department of internal combustion engines of National Technical University "Kharkiv Polytechnic Institute", Kharkiv, Ukraine.

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Published

2018-06-20

Issue

Section

Mathematical methods, models, problems and technologies for complex systems research