Neuro-fuzzy modeling the rate of international migration in 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 modeling. 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.