The demographic policy of the Russian Federation is aimed at increasing the population in the country. In this connection, management decisions made at the regional level focus at attracting skilled migrants, increasing the birth rate, and reducing mortality. On the one hand, such politics affects the size of the population; on the other hand, the reaction of the population can adjust the policy. In turn, state programs are intended for a long period of time, thus, there is a need to assess the effectiveness of the taken decisions. Therefore, the authors have proposed a concept of an agent-based model of demographic processes at the regional level. In addition, they have developed the model itself, which aims to increase the accuracy of forecasting the population in the face of changing socio-economic indicators. Each of the agents (represented by “Person” and “Region”) have their own set of characteristics. To describe the logic of the agent behavior, the authors have used statistical (regression and cluster analysis) and probability (Bernoulli, Gamma, Betta, exponential distribution) methods. The life cycle of the agent “Person” is presented in the developed state diagram. The testing of the agent-based model was performed in solving the problems of forecasting the population in the Republic of Bashkortostan on the basis of the prognosis data from the RF Ministry of Economic Development.
The article also presents experimental research on two scenarios of economic development (basic and conservative). An assessment of changes in fertility, mortality, and migration based on the use of cluster and regression analysis is presented.
ya||a: GPU-powered Spheroid Models for Mesenchyme and Epithelium
