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JOURNALS // Computer Research and Modeling // Archive

Computer Research and Modeling, 2015 Volume 7, Issue 4, Pages 923–939 (Mi crm269)

This article is cited in 3 papers

MODELS OF ECONOMIC AND SOCIAL SYSTEMS

Empirical testing of institutional matrices theory by data mining

I. L. Kirilyuka, A. I. Volynskya, M. S. Kruglovaa, A. V. Kuznetsovab, A. A. Rubinsteina, O. V. Sen'koc

a Institute of Economics of RAS, 32 Nakhimovsky prospect, Moscow 117218 Russia
b Emanuel Institute of Biochemical Physics of RAS, 4 Kosygina str., Moscow, 119334, Russia
c Dorodnicyn Computing Centre of RAS, 40 Vavilov str., Moscow, 119333, Russia

Abstract: The paper has a goal to identify a set of parameters of the environment and infrastructure with the most significant impact on institutional-matrices that dominate in different countries. Parameters of environmental conditions includes raw statistical indices, which were directly derived from the databases of open access, as well as complex integral indicators that were by method of principal components. Efficiency of discussed parameters in task of dominant institutional matrices type recognition (X or Y type) was evaluated by a number of methods based on machine learning. It was revealed that greatest informational content is associated with parameters characterizing risk of natural disasters, level of urbanization and the development of transport infrastructure, the monthly averages and seasonal variations of temperature and precipitation.

Keywords: institutional matrices theory, machine learning.

UDC: 51-77

Received: 20.02.2015
Revised: 08.04.2015

DOI: 10.20537/2076-7633-2015-7-4-923-939



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