DISCREPANCY PARAMETERS OF APPROXIMATIONS OF DISCRETELY SPECIFIED DEPENDENCIES BY ANALYTICAL FUNCTIONS AND SEARCH CRITERIA FOR OPTIMAL VALUES OF THEIR COEFFICIENTS

Author:

Zakharchenko S.M.ORCID, ,Shydlovska N.A.ORCID,Mazurenko I.L.ORCID, ,

Abstract

Universal discrepancy parameters of approximations of discretely specified dependencies by analytical functions and search criteria for optimal values of their coefficients, as well as analysis of features of their application are described. Discrepancy parameters of approximations, which do not depend on the ranges of variation of the values of functions and the number of points of a discretely specified dependence, are proposed. They can be effective for objectively comparing the quality of approximations of any dependencies by any functions. Approximations of a discretely specified dependence of the mathematical expectation of the equivalent electrical resistance of a layer of aluminum granules during spark-erosion dispersion in water on the instantaneous values of the discharge current are carried out. As approximating functions, we chose a power function with an exponent factor –1 and a function based on exponential. Using the criteria of the least approximation error, the optimal values of the coefficients of both approximating functions are founded. It is shown in which cases it is advisable to use the combined search criteria for the optimal values of the coefficients of the approximating functions, and in which are enough simple one-component ones. Ref. 27, fig. 2, tables 2.

Publisher

National Academy of Sciences of Ukraine (Co. LTD Ukrinformnauka) (Publications)

Reference27 articles.

1. 1. Zakharchenko S.N. Modelling of Dependence of Electrical Resistance of Granulated Current-carrying Mediums from a Pulse Current Proceeding in them. Tekhnichna Elektrodynamika. 2012. No 5. Pp. 17-27. (Rus)

2. 2. Linnik Yu.V. The least squares method and the foundations of the mathematical and statistical theory of observation processing. Moscow: State publishing house of physical and mathematical literature, 1962. 354 p. (Rus)

3. 3. Vinogradov V.N., Gai E.V., Rabotnov N.S. Analytical data approximation in nuclear and neutron physics. Moscow: Energoatomizdat, 1987. 128 p. (Rus)

4. 4. Least Squares Method. URL: https://ru.wikipedia.org/w/index.php?title=Metod_naimen'shih_kvadratov&stable=1. (accesstd: 12.07.2021. (Rus)

5. 5. Tsidelko V.D., Yaremchuk N.A. Measurement uncertainty. Data processing and presentation of the measurement result. Kyiv: Polіtekhnіka, 2002. 176 p. (Ukr).

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