Ensuring Reliability of Control Data in Engineering Systems

Author:

Dychko A.1,Yeremeyev I.2,Kyselov V.2,Remez N.1,Kniazevych A.3

Affiliation:

1. Institute of Energy Saving and Energy Management , National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” 37 Peremohy Ave., Kyiv , 03056 , Ukraine

2. Taurida National V.I. Vernadsky University 33 Ivana Kudri Str., Kyiv , 04000 , Ukraine

3. Stepan Demianchuk International University of Economics and Humanities 4Stepana Demianchuka Str., Rivne , 33027 , Ukraine

Abstract

Abstract The paper presents the approach of determination of rationality coefficients of control system, inputted uncertainty, control of the process, system errors, and uncertainty. Algorithms for identifying the states of system have been developed on the basis of theorems of identification. They actually implement the theoretical multiplication cross-section and establish that increasing the reliability of information is possible only through the use of redundancy (structural, procedural, and informational). The increase in the reliability of control data with the developed methods ensures significant improvement of the functioning of information systems and facilitates the adoption of more substantiated decision making.

Publisher

Walter de Gruyter GmbH

Subject

Psychiatry and Mental health,Neuropsychology and Physiological Psychology

Reference12 articles.

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3. 3. Zadeh, L.A., Fu, K.S., ---amp--- Tanaka, K. (2014). Fuzzy sets and their applications to cognitive and decision processes. In: Proceedings of the US–Japan Seminar on Fuzzy Sets and their Applications, University of California, Berkeley, California, 1–4 July 1974. Academic Press.

4. 4. Yager, R.R., ---amp--- Zadeh, L.A. (2012). An introduction to fuzzy logic applications in intelligent systems. Springer Science ---amp--- Business Media.

5. 5. Kofman, A. (1982). Introduction to the Theory of Fuzzy Sets. Radio and Communication. Moscow, SU.

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