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Reference:
Plokhotnikov K.E. —
Mathematical model of geopolitics
// World Politics.
– 2017. – № 3.
– P. 23 - 74.
DOI: 10.25136/2409-8671.2017.3.23674 URL: https://en.nbpublish.com/library_read_article.php?id=23674
Mathematical model of geopolitics
Plokhotnikov Konstantin Eduardovich
Doctor of Physics and Mathematics
Leading Research Fellow at the Department of Mathematical Modeling and Information Technology of Lomonosov Moscow State University, Professor at the Financial University under the Government of the Russian Federation
119991, Russia, Moscow, Leninskie Gory, MSU, Faculty of Physics, of. 2-40b
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psygma@yandex.ru
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DOI: 10.25136/2409-8671.2017.3.23674
Review date:
24-07-2017
Publish date:
04-09-2017
Abstract. Mathematical model of geopolitics is a conditional name of several models, which are naturally connected with and serve as companions to the main theme – geopolitics. The author introduces the central notion of a mathematical model of geopolitics – capacity of a habitat. Geopolitics includes climate, terrain, peculiarities of logistics of global flows of commodities, and geopolitical confrontation in terms of “sea – continent”, i.e. all those things composing the material set of conditions of existence of the population of the world. This set to a significant extent mediates political behavior of people. The author doesn’t adhere to the position of environmental determinism in the form of geopolitics, but tries to outline manifestations of geopolitics in the real politics. In all the demonstrated mathematical models, the author refers to a computational experiment, the results of which are presented and discussed in the text. The computational experiment is based on the data about climate, terrain, population and other components typical for modern geo-information systems. The mathematics of these models implies knowing the fundamentals: numerical methods, statistics, methods of optimization and some other disciplines. The author describes the density of habitat capacity in different countries. Par for the course, the top positions are taken by, in decreasing order, Russia, the USA, Brazil, China, Australia. The author defines and studies the index of specific capacity of habitat per capita, ranks countries and territories according to this index. Special attention is given to the correlation between these indexes in particular countries compared to Russia. The author studies the issue of interaction between the density of habitat capacity and terrain, compares territories concentrating 50% of the population and 50% of density of habitat capacity, and outlines the density gradient margins. The author classifies countries and territories in terms of “high – low” and “favourable – unfavourable”, i.e. in four categories taking account of terrain and density of habitat capacity. The paper contains the maps of territories of all four types. The author introduces and calculates the diversity index of particular territories and countries. Within the global traffic calculation, the author creates a specific index of percentage “sea – continent”. Based on this index, the author classifies points (territories) in geopolitical terms. This index helps formalize such well-known geopolitical notions as “Heartland” and “Rimland”. The author composes combined global and regional maps with political and geopolitical marking. These maps are analyzed for so-called geopolitical splits. Such splits are detected when some geopolitical lines don’t coincide with the state border, but lay deeply across its territory. The author demonstrates the numerical solution of the problem of optimal distribution of points (in terms of minimal transportation expenses) serving as logistics hubs on the planet.
Keywords:
cutting of territories, territories diversity index, Monte Carlo method, correlation analysis, terrain, minimax transport doctrine, density of population, capacity of habitat, geopolitical classification of points, non-linear optimization
This article written in Russian. You can find full text of article in Russian
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