1. Forecasting Efficiency of Programs and Optimization of Local Budgets in Smart Cities for a Better Quality of Life
- Author
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Oleg Pakhomov, Oleg Metsker, Georgy Kopanitsa, and Egor Trofimov
- Subjects
machine learning ,big data ,quality of life ,smart city ,modeling ,economy ,Telecommunication ,TK5101-6720 - Abstract
This paper presents the results of developing a machine learning model of migration of citizens to districts of the city of St. Petersburg. The models were built based on the dynamics of economic reporting indicators of districts, the territorial characteristics of municipal districts, and the characteristics of the flow of population itself. Correlations of these indicators with the quality of life were determined. Quality of life is certainly related to the characteristics of migration, emigration, and their ratio, as well as their dynamics as it is an objective indicator of the attractiveness of the municipal district. On the basis of the data of 2118 indicators in the dynamics from 17 to 20 years for 111 municipal districts managed to develop a model of machine learning in the indicator R-Squared: 0.74, RMSE: 414.73. Thus, it was possible to reveal the most significant indicators for improvement of quality of life of the population considering specificity of municipal district, structure of living population and structure of expenses in the unified system. The given model can be applied both for forecasting of quantity of migration and structure, and for decision-making on improvement of quality of life of the city population in view of specificity, dynamics, and budget of municipal districts. The results can be useful for regulatory policy and optimization of legal regulation.
- Published
- 2022
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