Metrics for Assessing the Quality of Numerical Parameters of Dynamic Systems

DOI: https://doi.org/10.25559/SITITO.019.202302.393-402

Abstract

The problem of uncertainty concerning the quality of input data describing the system is one of the most significant problems in the construction of control systems for complex objects. This problem is even more acute when managing poorly formalized systems. A critical component of data quality management is the development of metrics that inform consumers about the quality characteristics that are most important for assessing the degree of suitability of the data for use. The article suggests such parameters for measuring data quality as data accuracy, which is defined as the similarity of the characteristics of a data set with non-distorted characteristics of a real object, and data reliability, which is defined as the discrepancy between the characteristics of a data set with the characteristics of an object, for which all recorded parameters are absolutely random. Formulas for determining the measures of these quality parameters using the finite difference apparatus are given. The proposed methodology provides a fairly formalized and computationally simple algorithm for evaluating the quality of a set of input parameters of a complex dynamic system. The proposed estimates are effec-tive quality metrics, the analysis of which allows you to initiate a control algorithm that extracts a useful signal from a noisy data stream. The analysis shows that a significant number of the parame-ters under consideration have a significant registration error and an insufficient degree of reliability. Consequently, the use of such data as a basis for decision-making, without taking into account the existing distortions, introduces errors in estimates and forecasts and, as a result, leads to a significant decrease in the quality of management decisions. In particular, the calculation of composite system quality indices based on a single observation of statistical measurements using mathematical meth-ods does not imply the elimination of the existing noise component of the data, as a result of which the result obtained may be implausible.

Author Biography

Tatyana Valentinovna Zhgun, Yaroslav-the-Wise Novgorod State University

Associate Professor of the Department of Applied Mathematics and Computer Science, Institute of Electronic and Information Systems, Cand. Sci. (Phys.-Math.), Associate Professor

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Published
2023-06-30
How to Cite
ZHGUN, Tatyana Valentinovna. Metrics for Assessing the Quality of Numerical Parameters of Dynamic Systems. Modern Information Technologies and IT-Education, [S.l.], v. 19, n. 2, p. 393-402, june 2023. ISSN 2411-1473. Available at: <http://sitito.cs.msu.ru/index.php/SITITO/article/view/972>. Date accessed: 10 oct. 2025. doi: https://doi.org/10.25559/SITITO.019.202302.393-402.
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Issue
Vol 19 No 2 (2023): Modern Information Technologies and IT-education
Section
Research and development in the field of new IT and their applications
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