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Aleksandra Ravnachka; Velimira Stoyanova
•    Prof. DSc. Oleksandr Trofymchuk, UKRAINE 
•    Prof. Dr. hab. oec. Baiba Rivza, LATVIA
Cartography and GIS
The current research aims to apply cluster analysis using the software ArcGIS in the study of the food industry in Bulgaria for the period 2010 to 2020. The use of clustering methods is necessary to differentiate homogeneous groups of administrative-territorial units of NUTS 3 level on certain indicators to reveal several features and implement specific economic policies and measures for areas of a cluster and others. The grouping of the areas according to the considered indicators was done with the tool Grouping Analysis. Grouping and classification techniques are some of the most widely used methods in machine learning. We have selected No_spatial_constraint for the Spatial Constraints parameter, for grouping using the K-Means algorithm. Based on the results of the “average intergroup connection” method, the areas are grouped into 7 clusters (food industry, 2010 and 2020; food and beverage products for the period 2010-2020) and into 4 clusters (tobacco production for the period 2010-2020). The selection of indicators based on which the clusters are formed is following the generally accepted indicators for assessing the state and importance of the food industry in the structure of the economy and their information accessibility. The following indicators were used output for 2010 and 2020, employees for 2010 and 2020, and export earnings for 2010 and 2020 for the given territorial unit The territorial distribution of the population, in combination with the historical and modern economic development of the settlements, forms the regional differences in the development of the food industry in the country. The cluster analysis of certain indicators for the assessment of the food industry at the NUTS 3 level for 2010 and 2020 shows some change in the trends in the territorial development of the industry. The cluster analysis shows that there are slight territorial differences at the NUTS 3 level in food production, with large consumer centers and markets being the most important. In the activities of tobacco and beverage production, the territorial differences are minimal.
grouping analysis, statistical information, K-means clustering, employees, export
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Participation in SGEM is financed by the project "National Geoinformation Center (NGIC)" funded by the National Roadmap for Scientific Infrastructure 2017-2023 under Contract No D01-404/18.12.2020 with the Ministry of Education and Science of Bulgaria
Proceedings of 22nd International Multidisciplinary Scientific GeoConference SGEM 2022
22nd International Multidisciplinary Scientific GeoConference SGEM 2022, 04 - 10 July, 2022
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference SGEM
SWS Scholarly Society; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Serbian Acad Sci and Arts; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; European Acad Sci, Arts and Letters; Acad Fine Arts Zagreb Croatia; Croatian Acad Sci and Arts; Acad Sci Moldova; Montenegrin Acad Sci and Arts; Georgian Acad Sci; Acad Fine Arts and Design Bratislava; Turkish Acad Sci.
04 - 10 July, 2022