Neuro-fuzzy modeling the rate of international migration in Ukraine

Authors: G. Chornous, ORCID ID 0000-0003-4889-1247, Doctor of Sciences (Economics), Associate Professor, Department of Economic Cybernetics, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
V. Potapova, Economist, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine

Abstract: This article presents a new methodological approach for estimating the rate of international migration in Ukraine based on the experience of other territories and the application of neuro-fuzzy model ing. Firstly, using the results of previous studies, the factors affecting the decision of the person to migrate are determined. Following that, the most vital features found by regression- correlation analysis are used for grouping the countries into clusters in order to determine the list of states, which are similar to Ukraine with regards to migration climate. Based on the data of analogous countries, this study demonstrates the process of developing an adaptive neuro-fuzzy inference system (ANFIS) for modeling the migration rate in Ukraine and provides some recommendations for further research.

Key words: international migration, migration modeling, clustering, fuzzy logic, neuro-fuzzy modeling

Received: 09/07/19

1st Revision: 23/8/19

Accepted: 01/09/19

DOI: https://doi.org/10.17721/1728-2667.2019/205-4/7

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