Determination of Significant Parameters on the Basis of Methods of Mathematical Statistics, and Boolean and Fuzzy Logic

Yulia Shichkina, Mikhail Petrov and Fatkieva Roza
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Yulia Shichkina: Faculty of Computer Science and Technology, St. Petersburg State Electrotechnical University “LETI”, 197376 St. Petersburg, Russia
Mikhail Petrov: Faculty of Computer Science and Technology, St. Petersburg State Electrotechnical University “LETI”, 197376 St. Petersburg, Russia
Fatkieva Roza: Faculty of Computer Science and Technology, St. Petersburg State Electrotechnical University “LETI”, 197376 St. Petersburg, Russia

Mathematics, 2022, vol. 10, issue 7, 1-13

Abstract: Among the set of parameters for which data are collected for decision-making based on artificial intelligence methods, often only some of the parameters are significant. This article compares methods for determining the significant parameters based on the theory of mathematical statistics, and fuzzy and boolean logic. The testing was conducted on several test data sets with a different number of parameters and different variability of parameter values. It was shown that for data sets with a small number of parameters (<5), the most accurate result was given for a method based on the theory of mathematical statistics and boolean logic. For a data set with a large number of parameters—the most suitable is the method of fuzzy logic.

Keywords: logic; mathematical statistics; disjunctive perfect normal form; arithmetic average; membership function; significant parameters (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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