Fuzzy Logic Modelling Of The Russian Demographic Space

Abstract

Demographic processes are extremely difficult to manage and require the different methods of their research. Our studies aimed at modelling the demographic space of Russian regions by using fuzzy clustering. Our analysis is based on the indicators of the regions' demographic potential. We used our own original methodology combining the statistical procedures of fuzzy clustering and expert survey data. We considered indicators characterizing the reproduction potential and variables characterizing the potential quality of the future population. As a result of fuzzy clustering, five clusters were formed. Our experts evaluated the reproduction potential and the quality of the future population for each cluster. The data for each region were used to calculate their reproduction potential and the quality of their future population. In comparison to hard clustering, fuzzy clustering enhances the flexibility of evaluation: our assesments of each region do not depend exclusively on the potential of the nearest cluster, as we also take into consideration the region's possible similarities with other neighbouring clusters with different potential. Such modelling allows us to identify those Russian regions that could be considered as 'growth points' in the implementation of demographic policy.