Parametric clustering of cities

The article analyzes the master plans and functional areas of 42 cities from different federal districts of the Russian Federation. To identify the dependencies between the characteristics of localities and the allocation of functional zones in them, the data clustering method was applied. Also criteria for clustering were identified – these are quantitative characteristics that are universal for various localities: total area of a locality, population, population density and gross regional product. With these criteria clustering was carried out using the software package «Deductor», based on algorithms of neural network modeling. Self-organizing Kohonen maps (SOM) were used to visualize the obtained data. As a result of the clustering the connection between the characteristics of localities and the ratio of functional zones in them is revealed.

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Geoecological Assessment of the State of Soils in Functional Zones of the Territory of the Eastern Administrative Okrug of Moscow, the Russian Federation

E3S Web of Conferences ◽

10.1051/e3sconf/202128506009 ◽

2021 ◽

Vol 285 ◽

pp. 06009

Author(s):

S. V. Dubrova ◽

I. I. Podlipskiy ◽

P. S. Zelenkovskiy ◽

P. I. Egorov ◽

E. M. Nesterov

Keyword(s):

Urban Development ◽

The State ◽

Point Of View ◽

Functional Zone ◽

Functional Zones ◽

Preliminary Preparation ◽

The Russian Federation ◽

Functional Areas ◽

Territorial Division ◽

Functional Purpose

With the development of megalopolises, constant expansion of their borders and chaotic and – to a greater extent – unreasonable territorial division of lands, potential recreational areas are experiencing colossal anthropogenic load and can be found in the state of oppression, gradually moving into an industrial functional zone, from the environmental point of view. For the preservation of ecosystems and rational planning of urban development, it is necessary to pay special attention to the functional purpose and mode of use of the sites, which are the essence of zoning and governance in the field of urban development of land. This paper presents a geoecological assessment of the dynamics of changes in pollution halos among the functional areas of the Eastern Administrative Okrug of Moscow over the past 30 years. Geochemical series of pollutants were compiled with the help of methods of preliminary preparation and statistical data processing. A forecast of the spread of pollution in the surface horizon for the next 100 years is presented, taking into account the hydrogeological features of the territory of the Eastern Administrative Okrug of Moscow.

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National park «Zyuratkul» (Chelyabinsk region) functional zones correction along habitat borders of vertebrate rare species

FORESTRY BULLETIN ◽

10.18698/2542-1468-2021-2-41-50 ◽

2021 ◽

Vol 25 (2) ◽

pp. 41-50

Author(s):

A.R. Sibirkina ◽

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L.V. Trofimova ◽

N.N. Kuzmishchev ◽

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...

Keyword(s):

Endangered Species ◽

National Park ◽

Climatic Conditions ◽

Rare And Endangered Species ◽

Literary Sources ◽

Functional Zones ◽

Rare And Endangered ◽

The Russian Federation ◽

Chelyabinsk Region ◽

Functional Areas

Information on the18 species of vertebrates included in the Red Book of the Russian Federation and the Red Book of the Chelyabinsk Region habitats in the territory of the Zyuratkul National Park is presented. The developed system of functional zones in the Zyuratkul National Park is presented in order to ensure the safety of animals living on its territory. The analysis of literary sources describing the Red Book species of vertebrates inhabiting this territory is presented, on the basis of which the necessary requirements for their habitat are characterized and the climatic conditions formed in the studied territory are described. The general geographical features of the area are revealed, the laws of natural and economic territorial complexes are established. The established boundaries of the habitats of vertebrates are highlighted and plotted on schematic maps. Proposals have been developed to adjust the boundaries of previously defined functional areas. Proposals have been made for monitoring the number of rare and endangered species of vertebrates and monitoring anthropogenic load.

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The regions of Russia: specifics of socio-economic development

The Eurasian Scientific Journal ◽

10.15862/35ecvn121 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Tat’yana Pozdnyakova

Keyword(s):

Economic Development ◽

Russian Federation ◽

Federal District ◽

Federal State ◽

Gross Regional Product ◽

Socio Economic Development ◽

Federal Districts ◽

The Russian Federation ◽

Per Capita ◽

Regional Product

The Federal District, as the highest link in the economic zoning of the Russian Federation, is the most important element of the national economic system, which largely determines the features of its functioning. The article provides an overview of the internal differences of the federal districts of the Russian Federation in terms of gross regional product. This indicator is one of the most important indicators of the specificity of the socio-economic development of the regions, and also, to a certain extent, reflects the possibility of their balanced functioning. Based on the official data presented on the website of the Federal State Statistics Service, the federal districts of Russia were ranked according to the indicator under study and their typology was presented. Within the framework of this typology, groups are identified that reflect the differences between the constituent entities of the Russian Federation in the distribution of gross regional product per capita in federal districts with its value above or below the average Russian level, respectively. Within each federal district, entities with maximum and minimum values of gross regional product per capita were identified. On this basis, an intra-district imbalance coefficient is calculated, reflecting the degree of the gap in the levels of socio-economic development of the constituent entities of the Russian Federation within the corresponding federal district. A brief description of the federal districts belonging to two different types is given in terms of the balance of their socio-economic development. The general trend of dependence of the coefficient of intra-district imbalance on the level of regional development is shown. There are some features that need to be taken into account when formulating development programmes and strategies at the federal district gape.

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Neural network modeling of tourism development as a factor of sustainable economic growth in Russian regions

E3S Web of Conferences ◽

10.1051/e3sconf/202129102023 ◽

2021 ◽

Vol 291 ◽

pp. 02023

Author(s):

Elena Letiagina ◽

Valentina Perova ◽

Aleksander Gutko ◽

Aleksander Kutasin

Keyword(s):

Neural Network ◽

Russian Federation ◽

Economic Activity ◽

Dimensional Space ◽

Network Modeling ◽

Neural Network Modeling ◽

Russian Regions ◽

Tourism Sector ◽

The Russian Federation ◽

Regions Of Russia

The features of the development of the tourism sector in the regions of the Russian Federation, which have an impact on the socio-economic development of the country, have been investigated. Analysis of the current state of the tourism sector, classified as the main types of economic activity, is relevant and important for increasing the competitiveness of the regions of the Russian Federation and ensuring the economic security of the state. The study is aimed to model and analyze tourist cluster formations in Russia. The study of tourist activity in the regions of Russia based on the indicators of the database of the Federal State Statistics Service was carried out using a new promising approach - cluster analysis using the scientific and methodological apparatus of artificial neural networks. The distribution of Russian regions into five tourist clusters has been obtained as a result of clustering multidimensional data using neural networks - self-organizing Kohonen maps, which are focused on self-study, and modern information technologies. In neural network modeling, the six-dimensional space of tourism development indicators was mapped, taking into account the topology, into a two-dimensional space, which made it possible to visualize the results of grouping regions by tourist clusters. The features of the development of the tourism sector in the regions of the Russian Federation have been revealed by the totality of the considered indicators The obtained results state that there is a strong variation in the number of regions by tourist clusters and the ametric nature of the development of tourist activity in the regions of Russia. The results of the study are of practical significance for the strategic planning of the tourism sector development, which ensures the development of domestic and inbound tourism. Analysis of the functioning of the tourism sector in the regions of the Russian Federation allows concluding the necessity to take a set of measures to stimulate effective investment activity in a number of tourism clusters, harmonizing the strategies of the state and business, which will contribute to the renewal and competitiveness of this type of economic activity.

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Studying the innovative development of regional economy as an imperative of sustainable socio-economic growth in Russia, using neural network modeling

Economic Analysis Theory and Practice ◽

10.24891/ea.20.8.1394 ◽

2021 ◽

Vol 20 (8) ◽

pp. 1394-1414

Author(s):

Nikolai P. LYUBUSHIN ◽

Elena N. LETYAGINA ◽

Valentina I. PEROVA

Keyword(s):

Neural Network ◽

Economic Growth ◽

Neural Networks ◽

Russian Federation ◽

Network Modeling ◽

Innovation Activity ◽

Neural Network Modeling ◽

Innovative Development ◽

Russian Regions ◽

The Russian Federation

Subject. The article deals with the innovative potential of Russian regions in light of the national goal of the Russian Federation development, reflecting decent and productive work. Objectives. The purpose is to study the innovation activity in Russian regions, using neural networks, to ensure breakthrough innovative development of the Russian economy. Methods. We employ a cluster analysis on the basis of neural network modeling, using information technologies. For the research, we selected neural networks (Kohonen self-organizing maps), which are focused on unsupervised learning and are a promising tool for clustering and visualization of multidimensional statistical data. Results. The result of neural network modeling was the ranking of 85 regions of the Russian Federation into 5 compact groups (clusters) regardless of their affiliation to federal districts of the Russian Federation. The study shows that there is a strong differentiation of the number of regions in these clusters. We obtained average values of indicators in the clusters and compared them with all-Russian indicators. Conclusions. Breakthrough in the socio-economic growth of the Russian Federation is associated with a set of measures that involve stimulating innovation activities in regions, which are characterized by different level of innovation development. Such measures will increase the interest of the real sector of the economy in using scientific development, advanced production technologies, higher-productivity employment opportunities, and, as a result, will encourage socio-economic growth and people's quality of life.

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