The Problem of Clustering Countries of the World on the Geopolitical Data

Smirnov, Ivan; Malafeyev, Oleg; Smirnova, Tatiana; Yakovets, Yu V; Strekopytov, Sergei

doi:10.1088/1757-899x/1079/6/062066

Cited by 1 publication

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For illustration purposes, the study's results were visualized and an overview of the composition of the final clusters (Pichugin, 2018). The current work is a development and improvement of the previous one (Smirnov et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Researching Of Trends In The Development Of The Current Geopolitical Situation

Malafeyev¹,

Smirnov²,

Зайцева³

et al. 2022

Proceedings of the III International Conference on Economic and Social Trends for Sustainability of Modern Society – (ICEST-III

View full text Add to dashboard Cite

One of the forecasting tools in geopolitics is mathematical models. In this article, we have presented our own spatial model of geopolitical interactions. The model is based on the models of the geopolitical of the geopolitical position of Arzruni-Komlas and the meta-ethnic borderland of P. Turchin. For empirical verification of the proposed modifications, spatial data describing various properties of the planet Earth were collected and processed. These data include information about the relief of the Earth's surface, temperature, soil fertility capacity, degree of urbanization, land and sea surfaces, political affiliation. The results of modeling these geopolitical interactions on the example of a map of Europe with the inclusion of a part of North Africa have a very average nature of approximation to historical reality. Over the course of several hundred iterations, we managed to get very conditionally closer to the outlines of the political borders in this region. Obtaining more accurate results requires a better selection of model parameters and its possible refinement. The spatial model of geopolitical interactions we have built has proved to be quite workable. The model clearly demonstrated the influence of geographical and climatic data on the territorial distribution of the borders of state agencies. Due to the complexity and non-linearity of the considered problem of territorial dynamics of each particular state, it is difficult to assume how the position of borders will change in reality.

show abstract

Section: Introductionmentioning

confidence: 99%