Full Article: PDF
Scientific Object Identifier: http://s-o-i.org/1.1/TAS-09-125-39
DOI: https://dx.doi.org/10.15863/TAS.2023.09.125.39
Language: Russian
Citation: Zhanatauov, S. U. (2023). Cognitive model: corruption. ISJ Theoretical & Applied Science, 09 (125), 332-355. Soi: http://s-o-i.org/1.1/TAS-09-125-39 Doi: https://dx.doi.org/10.15863/TAS.2023.09.125.39 |
Pages: 332-355
Published: 30.09.2023
Abstract: Zharov S.N. [1] for the first time conducted a scientific analysis (from a legal point of view) of a little-known publication proposed by I.P. Liprandi [2] on a number of special types of corruption. The article develops a Cognitive model of the phenomenon of “corruption” in 2 versions, differing in sets of meanings of factors and their quantities. In each version, a system of semantic equations has been developed, each system consists of 3 semantic equations. One semantic equation has 4 known z-sense (semantic z-variables) variables and 1 unknown y-sense (semantic y-variable) variable. The system of semantic equations has 12 parameters that are extracted from the model matrices C55, C99; the matrices C55, C99 are modeled when solving Optimization Problems: (I55, I55) =>(?55, C55), (I99, I99) =>(?99, C99). Due to the discrepancy between the number of z-variables and the number of y-variables: 4(5, 4(9, there was a need for cognitive modeling of semantic equality meaning(ZZm4)=meaning(YYm3CCТ34) instead of equality meaning(ZZm5)=meaning(YYm5CCТ55). An algorithm has been developed for calculating the values of 4 zz-variables (instead of z-variables), depending on 24 values of 3 y-variables y2,y3,y4 (which have values of their variances close to 0). Random values of 3 y-variables y2,y3,y4 are modeled separately and independently of other model matrices. Constructing new meanings of y-factors of the phenomenon of “corruption” with the 1st option of the composition of corruption factors (4 zz-factors (for the “bottom”) and 5 y-factors (for the “top”) and construction with the 2nd option of the composition of corruption factors (4 zz-factors (for the “bottom”) and 9 y-factors (for the “tops”) made it possible to clarify situations of corruption, to understand new additional factors of corruption ((extract knowledge)). Visualization of the mutual dynamics of corruption factors showed the sameness of the model results of 2 variants of the corruption model. In terms of meanings and mutual dynamics of their values, the factors quantitatively reflect real situations of the phenomenon of corruption.
Key words: multisense equation with known and unknown semantic variables, Cognitive Model of the Phenomenon “Corruption”.
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