TYPOLOGIZATION OF THE ECONOMIC POTENTIAL AND DEVELOPMENT CHARACTERISTICS OF THE DISTRICTS OF SURKHANDARYA REGION BASED ON STATISTICAL AND NEURAL NETWORK APPROACHES
DOI:
https://doi.org/10.5281/zenodo.20449576Keywords:
investment activity, economic disparities, territorial typology, district clustering, economic potential, K-means, Self-Organizing Map.Abstract
This article develops a multidimensional typology of the economic potential and development characteristics
of the districts of Surkhandarya region based on statistical data for 2010-2024. In the study, indicators reflecting the
economic condition and development dynamics of the territories were standardized, and the Ward method, K-means
clustering, and Self-Organizing Map (SOM) approaches were applied. The results show that the territories of the region
are divided into three main typological groups: industrialized districts with high entrepreneurial activity, districts dominated
by an agrarian orientation, and territories with relatively high levels of efficiency and growth rates. The scientific novelty
of the study lies in the deeper identification of interterritorial economic disparities by integrating traditional statistical
clustering methods with the SOM-based neural network approach.
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