Abstract
A complex study of the state of the main transport systems of the subjects of the Southern Federal Region of the Russian Federation was carried out using fuzzy modeling. The information base for the study was the annual data on the main indicators of the characteristics of vehicles in the region for 2010–2016. The investigated indicators were considered in the form of relative indicators as a quotient of the division of their values into the sizes of the areas of the relevant subjects of the region. Then, estimates of the values of the indicators for 2016 were constructed as expected or desired in comparison with the largest values of the corresponding indicators per unit area of the subjects. Using the corresponding weight coefficients of the indicators and their expected estimates, fuzzy sets for the investigated indicators of each region’s subject were determined. In order to identify the best subject of the region in terms of the state of the transport system in 2016, the maximin convolution method is applied. The received estimations have allowed to rank subjects of the region on a level of development of their transport systems. Also the analysis of transport systems of subjects and in the whole region is carried out taking into account the positive and negative dynamics of indicators based on their growth rates. The results of this analysis create the possibility of developing a strategy for the development of the region’s transport system.
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Acknowledgements
The research is conducted with a support of the Russian Foundation for Basic Research (#17-20-04236 ofi_m_RJD).
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Bogachev, T., Alekseychik, T., Bogachev, V. (2019). Comparative Assessment of the Transport Systems of the Regions Using Fuzzy Modeling. In: Aliev, R., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Sadikoglu, F. (eds) 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. ICAFS 2018. Advances in Intelligent Systems and Computing, vol 896. Springer, Cham. https://doi.org/10.1007/978-3-030-04164-9_85
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DOI: https://doi.org/10.1007/978-3-030-04164-9_85
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