Combination of analytical and agent-based modeling in studying migration processes in the Arctic regions of Eurasia

4th International Scientific Conference "Arctic: History and Modernity"

生态环境科学;历史学

Bystrov, V.^1 ; Malygina, S.^1^2 ; Shishaev, M.^1^3 ; Maevsky, D.^4

Institute for Informatics and Mathematical Modeling, Subdivision of the Federal Research Centre, Kola Science Centre, Russian Academy of Sciences, Apatity, Russia^1

Apatity Branch of Murmansk Arctic State University, Apatity, Russia^2

Murmansk Arctic State University, Murmansk, Russia^3

Omsk State Technical University, Omsk, Russia^4

关键词: Analytical and simulation model;    Computational experiment;    Forecasting methods;    Level of abstraction;    Migration process;    Robust identification;    Socio-economic systems;    Statistical characteristics;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/302/1/012085/pdf
DOI  :  10.1088/1755-1315/302/1/012085

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The article is devoted to the development of forecasting methods for the research on migratory processes. The authors pay attention to specific problems of migration in the Arctic regions of Eurasia. It is proposed to use a combination of analytical and simulation modeling to enhance the quality of prognoses for migration flows. Two parts of the ongoing research are described: technology of entropy-robust identification of the parameters of simulation models and a set of simulation models. The technology of entropy-robust assessment is based on the idea of re-use of formalized knowledge in the analysis of statistical characteristics of the parameters of simulation models. The technology allows to shorten the time and reduce the complexity of development of appropriate simulation models of migration. The complex of simulation models is developed on the basis of a combination of system dynamics, discrete-event and agent-based modeling. The integration of agent-based and analytical modeling to create simulation models of migration processes allows, on the one hand, to ensure the accuracy of the simulation according to the quality of the source data, and on the other, to analyze socioeconomic systems at the required level of abstraction. The results of computational experiments to identify trends in migratory processes in the Arctic regions are presented.