Open AccessModelling of Optimization of Conditions for the Transition of a Megalopolis to a Cluster Group with the Best Quality of Life Indicators
Author(s) -
S. A. Ershova,
T. N. Orlovskaya
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1079/2/022081
Subject(s) - megalopolis , ranking (information retrieval) , cluster analysis , cluster (spacecraft) , per capita , index (typography) , regression analysis , geography , econometrics , statistics , economics , mathematics , computer science , demography , economic geography , population , sociology , world wide web , programming language , machine learning
The article presents the results of a cluster assessment of Russian megalopolises based on the indicators of the human development index and the quality of life of residents. Based on the calculated data of cluster analysis, a model for optimizing the conditions for the transition of a megalopolis to a higher-ranking cluster group has been developed. The optimization model uses the most significant indicators for the city’s economy: the income index, per capita income, and the subsistence minimum. According to the modelling results, there have been composed the regression equations for the HDI of the megalopolis and regression equations for the multidimensional average of socio-economic indicators of the megalopolis. The authors have calculated the indicators of growth factors necessary for the transition of a megalopolis to a higher-ranking cluster and compiled a forecast matrix for clustering megalopolises with changed factors.